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Last updated on July 4, 2023. This conference program is tentative and subject to change
Technical Program for Wednesday July 12, 2023
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WePL |
Main Hall |
Is Resilience a Quality or a Quantity? |
Plenary Session |
Chair: Sawaragi, Tetsuo | Kyoto Univ |
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08:30-09:30, Paper WePL.1 | |
Is Resilience a Quality or a Quantity? |
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Hollnagel, Erik | Macquarie University |
Keywords: Cognitive aspects of automation systems and humans
Abstract: The question is essential and not just rhetorical. It is essential because we tend tacitly to accept the statement of William Thompson (aka Lord Kelvin) that:”Qualitative knowledge is real, but... quantitative knowledge is almost always better.” Since 1891, We have therefore conventionally but wrongly assumed that we cannot understand something unless we can measure it, even though it actually is the other way around. Namely, that we cannot measure something unless we fully understand it first. Quality must therefore precede quantity. Whether resilience is one or the other also leads to different questions, if resilience is assumed to be a quantity, the essential question is simply “how much resilience is there”. “But if resilience is a quality the essential question becomes just “how does resilience come about”. The answer to the latter question is clearly more important for engineering, for design and for control!
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WeA01 |
Main Hall |
Intelligent Robotics |
Regular Session |
Chair: Lygeros, John | ETH Zurich |
Co-Chair: Matsubara, Takamitsu | Nara Institute of Science and Technology |
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10:00-10:20, Paper WeA01.1 | |
Drone-Based Volume Estimation in Indoor Environments |
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Balula, Samuel | ETH Zurich Automatic Control Laboratory |
Liao-McPherson, Dominic | The University of British Columbia |
Stevšić, Stefan | Tinamu Labs |
Rupenyan, Alisa | ETH Zurich |
Lygeros, John | ETH Zurich |
Keywords: Information and sensor fusion, Intelligent robotics, Mobile robots
Abstract: Volume estimation in large indoor spaces is an important challenge in robotic inspection of industrial warehouses. We propose an approach for volume estimation for autonomous systems using visual features for indoor localization and surface reconstruction from 2D-LiDAR measurements. A Gaussian Process-based model incorporates information collected from measurements given statistical prior information about the terrain, from which the volume estimate is computed. Our algorithm finds feasible trajectories which minimize the uncertainty of the volume estimate. We show results in simulation for the surface reconstruction and volume estimate of topographic data.
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10:20-10:40, Paper WeA01.2 | |
Tactile Exploration Using Unified Force-Impedance Control |
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Karacan, Kübra | MIRMI/TUM |
Grover, Divij | Technical University of Munich |
Sadeghian, Hamid | Technical Univ. of Munich |
Wu, Fan | Technical University of Munich |
Haddadin, Sami | Technical University of Munich |
Keywords: Intelligent robotics, Autonomous robotic systems, Robotics technology
Abstract: Tactile robots can perform complex interaction skills, e.g., polishing. Such robots should therefore be designed to be adaptive to environmental uncertainties such as changing geometry and contact-loss. To address this, we propose a tactile exploration technique to observe the local curvatures of the physical constraints such as corners, edges, etc. for updating predefined tactile skill policies accordingly. First, we develop a unified force-impedance control approach in which the force controller significantly improves the geometry following performance due to the ensured contact. Second, we use the proposed controller to autonomously investigate the unknown environment via the local curvature observer, designed to be a dynamic process. Finally, the exploration performance of the proposed controller is demonstrated by using a polishing skill on an unknown 3D surface, where the robot is observed to autonomously investigate the unknown surface from top to bottom along the edges and corners.
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10:40-11:00, Paper WeA01.3 | |
Learning Re-Grabbing Policies Based on Grabbed Garbage Weight Estimation Using In-Bucket Images for Waste Cranes |
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Sasaki, Hikaru | Nara Institute of Science and Technology |
Watanabe, Go | Hitachi Zosen Corporation |
Hirabayashi, Terushi | Hitachi Zosen Corporation |
Kawabata, Kaoru | Hitachi Zosen Corporation |
Matsubara, Takamitsu | Nara Institute of Science and Technology |
Keywords: Intelligent robotics, Perception and sensing
Abstract: The automation of waste cranes has been demanded to perform garbage incineration work with fewer workers efficiently. In particular, data-driven learning approaches are desirable for waste crane automation. When deciding whether to re-grab garbage by a waste crane to grab more garbage, human operators are efficiently making decisions based on visual information. However, the current automation system has to lift up the bucket to measure grabbed garbage weight to decide re-grab. The lifting motion after grabbing makes the crane motion inefficient. For this limitation, we propose a re-grabbing decision system with feedback from in-bucket camera images for the efficiency of waste crane automation by introducing the vision sensor in the bucket. To simplify the decision process of re-grabbing, we separate the re-grabbing decision system from the in-bucket image into grabbed garbage weight estimation and the re-grabbing decision policy based on estimated garbage weight. Moreover, the weight estimator model and the re-grabbing policy model are designed based on a Bayesian manner for data efficiency. The effectiveness is verified in a robotic waste crane system with an in-bucket camera. We confirmed the proposed method could learn re-grabbing decisions from the autonomously collected data. It achieved more efficient re-grabbing by waste cranes than the conventional automated system.
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11:00-11:20, Paper WeA01.4 | |
DNN-Based Velocity Estimator Using Inertial Sensor for Robot Localization |
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Kim, Chul Hong | Seoul National University |
Cho, Dong-il Dan | Seoul National Univ |
Keywords: Mobile robots
Abstract: This paper presents an inertial sensor-based localization method using a deep neural network (DNN)-based velocity estimator. Among various sensors commonly used in localization, inertial sensors are less affected by the surrounding environment. The inertial sensor consists of an accelerometer and a gyroscope, which can estimate the poses of a robot. However, inertial sensors need to be used with other sensors for localization because inherent large drift errors are difficult to prevent. To overcome this problem, a DNN-based velocity estimator that reduces the position error by learning the data pattern of the inertial sensor and by limiting the range of the estimated velocity is proposed. The DNN-based velocity estimator comprises a convolutional neural network, a fully connected layer, and a smoothing filter. To limit the range of the estimated velocity, the range of velocity is divided by the total number of classes, and the divided range is assigned to each class. The relationship between consecutive classes is learned using a smoothing filter. Dataset-based experiments are performed to train the DNN-based velocity estimator and to evaluate the performance of the proposed localization. The experimental result shows that the proposed localization reduces the position errors by 99% compared to integration-based localization and by 91% compared to extended Kalman filter-based localization.
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11:20-11:40, Paper WeA01.5 | |
GMP-SLAM: A Real-Time RGB-D SLAM in Dynamic Environments Using GPU Dynamic Points Detection Method |
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Hu, Zhanming | Beijing Institute of Technology |
Fang, Hao | Beijing Institute of Technology |
Zhong, Rui | Beijing Institute of Technology |
Wei, Shaozhun | Beijing Institute of Technology |
Xu, Bochen | Beijing Institute of Technology |
Dou, Li-Hua | Beijing Institute of Technology |
Keywords: Autonomous robotic systems, Perception and sensing, Robotics technology
Abstract: Simultaneous Localization and Mapping (SLAM) is a fundamental technology for robotics. Vision-based SLAM has been developed for many years, but it is still difficult for SLAM system to handle dynamic environments. In this paper, we present GMP-SLAM, a real-time RGB-D SLAM system for highly dynamic environments with the help of GPU Grid Map Projection— a GPU dynamic points detection method we design. SLAM is a time-sensitive system for robotics, and it is hard to reach real time, especially in dynamic environments because it is necessary to track moving objects and it takes a lot of time. GMP-SLAM is based on ORB-SLAM2, which is one of the best feature-based SLAM frameworks and can reach real time just in CPU. But ORB-SLAM2 cannot handle highly dynamic environments very well, and most work focus on tracking moving objects with a neural network, which cannot reach real time even with the help of GPU. To solve real-time problem, we propose an all-in-parallel dynamic points detection framework for visual simultaneous localization and mapping (VSLAM) in dynamic environments based on 3D occupancy grid maps. Our SLAM system can provide not only higher trajectory accuracy but also a 3D grid map for navigation. We test our SLAM system in our real-world datasets we record and get higher trajectory accuracy than ORB-SLAM2. At the same time, our system can run nearly in 20Hz, which is much better than existing VSLAM framework in dynamic environments.
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11:40-12:00, Paper WeA01.6 | |
Feature Descriptor Based on Differential Evolution for Visual Navigation in Dynamic Environments |
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Lins Alves da Silva, Adriel Filipe | UFPE |
Ribeiro Araujo, Aluizio Fausto | Universidade Federal De Pernambuco - Ufpe |
Durand-Petiteville, Adrien | Federal University of Pernambuco UFPE |
Rodrigues Mendes, Cicero Samuel | Universidade Federal De Pernambuco |
Keywords: Intelligent robotics, Mobile robots, Evolutionary algorithms in control and identification
Abstract: This work proposes to use a teach-and-repeat method to navigate in an outdoor environment. Instead of using state-of-the-art feature point descriptors to match the current images to the database, we rely on the Generated Binary Robust Independent Elementary Features (GRIEF), a model robust to changes in illumination and weather. These descriptors are obtained via a training process employing evolutionary methods and binary comparison tests. The objective is to obtain visual feature descriptors designed for a given task. For the teach-and-repeat task, they are trained to optimize the estimate of the robot heading error with respect to a learned path. In this work, we propose to investigate how Differential Evolution (DE) can improve the performance of the GRIEF in terms of the convergence rate during the training phase and of fitness score. The new approach, named GRIEF-DE, is trained with the Michigan data set, made of pictures of an outdoor environment with significant changes in appearance caused by seasonal weather variations and illumination, and compared with the original GRIEF. The proposed model was applied to 4 different data sets and the experimental results suggest that the use of Differential Evolution improves the training performance as well as the estimation of the robot orientation with respect to the path of reference.
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WeA04 |
Room 303 |
Positive Systems |
Regular Session |
Chair: Ogura, Masaki | Osaka University |
Co-Chair: Ebihara, Yoshio | Kyushu University |
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10:00-10:20, Paper WeA04.1 | |
Asymmetric and Fitted Dissipativity with Logarithmic Storages for Positive Systems Exhibiting Interior Equilibria |
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Ito, Hiroshi | Kyushu Institute of Technology |
Keywords: Lyapunov methods, Stability of nonlinear systems, Control of interconnected systems
Abstract: This paper aims to develop a dissipativity-based framework for analysis of interconnection of scalar systems defined for positive variables exhibiting interior equilibria. To analyze asymptotic stability of an interconnected system, dissipativity-based approaches aggregate supply rates of component systems. This paper focuses on the fact that changes of parameters in component systems having interior equilibria can violate not only the stability, but also the positivity of variables. This paper peruses supply rates whose combination leads to a criterion with which the stability and the positivity can be verified simultaneously. Properties of supply rates suitable for logarithmic storage functions are investigated. It is explained how stability analysis leads us to a wrong conclusion if the positivity is forgotten. Based on those observed essentials, this paper proposes several asymmetric supply rates carrying the positivity information. Their usefulness is demonstrated through global and semi-global analysis of feedback interconnections, cyclic networks and a model of infectious diseases.
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10:20-10:40, Paper WeA04.2 | |
Definitions of Internal/External Positivity of Sampled-Data Systems and the Necessary and Sufficient Conditions |
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Shiga, Ryosuke | Kyoto University |
Hagiwara, Tomomichi | Kyoto Univ |
Ebihara, Yoshio | Kyushu University |
Keywords: Positive systems, Linear systems, Time-varying systems
Abstract: This paper extends the theory of positive systems to sampled-data systems. When considering positivity of LTI systems, where to take the initial time is unimportant. However, since sampled-data systems are periodically time-varying systems from the perspective of the continuous-time input and output signals, it is important to consider which time should be viewed as the initial time. Therefore, this paper studies positivity of sampled-data systems first by considering the case where a sampling instant is viewed as the initial time, and secondly by further considering the case where an arbitrary intersample instant is viewed as the initial time. The two different situations lead to quite relevant issues of what to take as the initial conditions and what to assume on the initial conditions in appropriately defining the internal/external positivity of sampled-data systems. These arguments are combined to derive the necessary and sufficient conditions for ultimate notions of (i.e., initial-time-independent) internal/external positivity of sampled-data systems.
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10:40-11:00, Paper WeA04.3 | |
Impulse-To-Peak Optimization of Positive Linear Systems Via DC Programming |
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Zhao, Chengyan | Ritsumeikan University |
Gong, Xin | The University of Hong Kong |
Ebihara, Yoshio | Kyushu University |
Ogura, Masaki | Osaka University |
Keywords: Positive systems, Linear systems, Optimization and control of large-scale network systems
Abstract: This paper is concerned with the optimization of the impulse-to-peak value of positive linear systems. Although the results of the analysis of the peak value of positive linear systems have been reported in the literature, the synthesis problem of impulse-to-peak value remains unresolved. To address this problem, in this paper we show that a cost-constrained minimization problem of the impulse-to-peak value of parameterized positive linear systems can be reduced to a DC (difference of convex functions) program. The derivation utilizes the log-log convexity of posynomial functions and a recent characterization of the impulse-to-peak value of positive systems via a linear program. To illustrate the effectiveness of our results, we study the optimization problem for minimizing the peak infection of networked epidemic spreading processes.
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11:00-11:20, Paper WeA04.4 | |
Observer-Based Control Design for Systems with Potentially Metzler Dynamics |
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Krokavec, Dusan | Technical University of Kosice |
Filasova, Anna | Technical University of Kosice |
Keywords: Positive systems, Observers for linear systems, Linear multivariable systems
Abstract: In this paper are solved problems concerning the state estimation in observer-based control of ostensible positive linear systems. The method is based on a composed form of the system matrix representation, where the constructive procedure is given to the observer synthesis. The method is flexible and allows to obtain the observer with the gain matrix being strictly positive. The design is computationally simple and reduces to feasibility of the LMI problem. Numerical simulation is presented to illustrate the validity of the proposed method.
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11:20-11:40, Paper WeA04.5 | |
Modelling and Control of COVID-19 in Small Environments with Two-Group Population |
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Niu, Zirui | Imperial College London |
Scarciotti, Giordano | Imperial College London |
Keywords: Healthcare management, disease control, critical care, Control in system biology, Systems biology
Abstract: How to maximise socioeconomic activities while retaining the effect of COVID-19 endemic under control is an essential topic when many countries have decided to live with COVID. In this paper, we show how optimal control can be used to classify the importance of non-pharmaceutical interventions (NPIs) to counter an epidemic under different expectations. We focus on the modelling of small environments, such as schools, universities, and care homes, where the population can be separated into two distinctive subgroups. We propose a model for such a scenario, we compute the associated basic reproduction number and we provide conditions for stability. Finally, we formulate an optimal control problem and, by means of simulations, we show that the relative importance of the interventions naturally emerges from the optimal policy.
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11:40-12:00, Paper WeA04.6 | |
External Positivity of Linear Systems: Approximate Characterization Via Convex Polytopes |
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Weller, Steven R. | University of Newcastle |
Keywords: Positive systems, Linear systems
Abstract: A linear system is said to be externally positive if the system output is non-negative for all time when driven by a non-negative input from the zero initial state. External positivity is well known to be equivalent to non-negativity of the impulse response and hence monotone nondecreasing step response. Despite the apparent simplicity of characterizing systems with non-negative impulse response, the determination of necessary and sufficient conditions for external positivity from a given transfer function is a long-standing open problem. In this paper, we propose a method which approximately characterizes the true region capturing the numerator polynomials of all (strictly proper) externally positive linear systems whose specified poles are assumed to satisfy a known necessary condition for external positivity. We compute an (outer) approximation of the true region via the construction of a convex polytope, each facet of which is contained in a supporting hyperplane of the true region. The proposed method requires only modest computational effort; has an accuracy which can be increased readily; applies to systems having orders n geq 4 for which no general characterizations of external positivity are currently known; and handles systems with complex poles (possibly repeated). Numerical examples illustrate the effectiveness of the proposed method.
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WeA05 |
Room 304 |
Towards a Systems Theory of Algorithms |
Invited Session |
Chair: Liao-McPherson, Dominic | The University of Michigan |
Co-Chair: Belgioioso, Giuseppe | ETH Zürich |
Organizer: Liao-McPherson, Dominic | The University of British Columbia |
Organizer: Belgioioso, Giuseppe | ETH Zürich |
Organizer: Dorfler, Florian | Swiss Federal Institute of Technology (ETH) Zurich |
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10:00-10:20, Paper WeA05.1 | |
Perception-Based Sampled-Data Optimization of Dynamical Systems (I) |
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Cothren, Liliaokeawawa | University of Colorado Boulder |
Bianchin, Gianluca | Université Catholique De Louvain |
Dean, Sarah | UC Berkeley |
Dall'Anese, Emiliano | University of Colorado Boulder |
Keywords: Data-based control, Convex optimization, Output regulation
Abstract: Motivated by perception-based and sensing-based control problems in autonomous systems, this paper addresses the problem of developing feedback controllers to regulate the inputs and the states of a dynamical system to optimal solutions of an optimization problem when one has no access to exact measurements of the system states. In particular, we consider the case where the states need to be estimated from high-dimensional sensory data received only at some time instants. We develop a sampled-data feedback controller that is based on adaptations of a projected gradient descent method and includes neural networks as integral components to estimate the state of the system from perceptual information. We derive sufficient conditions to guarantee (local) input-to-state stability of the control loop. Moreover, we show that the interconnected system tracks the solution trajectory of the underlying optimization problem up to an error that depends on the approximation errors of the neural network and on the time-variability of the optimization problem; the latter originates from time-varying safety and performance objectives, input constraints, and unknown disturbances.
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10:20-10:40, Paper WeA05.2 | |
Influence of Discretization in Dynamically Embedded Model Predictive Control (I) |
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Gautam, Yaashia | University of Colorado Boulder |
Nicotra, Marco M. | University of Colorado Boulder |
Keywords: Real-time optimal control, Nonlinear predictive control, Stability of nonlinear systems
Abstract: The paper analyzes the closed-loop stability of Dynamically Embedded Model Predictive Control for input-constrained continuous-time nonlinear systems. Given a stabilizing continuous-time optimal control problem, the proposed method performs a discrete approximation to obtain a finite number of optimization variables. The resulting optimization problem is then embedded into a dynamic feedback law that evolves in parallel to the system. Using Input-to-State Stability, it is shown that the dynamic interconnection between the ideal continuous-time model predictive controller and the dynamically embedded solver is asymptotically stable for a sufficiently small discretization step and sufficiently fast solver dynamics. Numerical results, however, highlight a counter-intuitive behavior: as the discretization step decreases, the stability of the closed-loop system tends to deteriorate. This suggests that, although the discretization should be sufficiently accurate to correctly capture the behavior of the system, oversampling the system dynamics may be just as harmful as undersampling.
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10:40-11:00, Paper WeA05.3 | |
A Framework for Decentralized Equilibrium Seeking in Networked Sampled-Data Games Using Hybrid Control Tools (I) |
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Shenoy, Vishal | University of California, San Diego |
Poveda, Jorge I. | University of California, San Diego |
Keywords: Differential or dynamic games, Networked systems, Sampled-data control
Abstract: We study the steady-state Nash equilibrium-seeking problem for sampled-data games with LTI dynamics and quadratic costs. The key challenge is to guarantee the robust stability and convergence properties of the closed-loop system in the presence of local individual sampling mechanisms assigned to each of the players in the game. This problem is non-trivial due to the unstable behaviors that can arise when sequential control updates (rather than parallel) emerge in the closed-loop system because of the existence of local control triggering mechanisms in each node of the network. To address this issue, we introduce a control framework based on tools from hybrid dynamical systems theory. Our results are illustrated via numerical examples.
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11:00-11:20, Paper WeA05.4 | |
Controller Design for Game Theoretic Steady-State Control: An LMI Approach (I) |
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Romano, Andrew | University of Toronto |
Pavel, Lacra | Univ of Toronto |
Keywords: Differential or dynamic games, Control of interconnected systems, Decentralized control
Abstract: We consider a set of LTI agents subject to constant external disturbances seeking to minimize coupled cost functions in steady-state, modelled as a game-theoretic problem. Using a novel framework, the Nash equilibrium seeking problem has been shown to reduce to the design of a set of decentralized stabilizing controllers. Herein, we consider two such controller designs, based off LMI approaches. The first employs a diagonal stability argument, and the second relies on H-infinity design coupled with the small gain theorem. Applications to sensor networks are provided and the trade-offs between the two methods are discussed.
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11:20-11:40, Paper WeA05.5 | |
Adaptive Decision-Making with Constraints and Dependent Losses: Performance Guarantees and Applications to Online and Nonlinear Identification (I) |
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Muehlebach, Michael | Max Planck Institute for Intelligent Systems |
Keywords: Adaptive control, Differential or dynamic games, Control problems under conflict and/or uncertainties
Abstract: We consider adaptive decision-making problems where an agent optimizes a cumulative performance objective by repeatedly choosing among a finite set of options. Compared to the classical prediction-with-expert-advice set-up, we consider situations where losses are constrained and derive algorithms that exploit the additional structure in optimal and computationally efficient ways. Our algorithm and our analysis is instance dependent, that is, suboptimal choices of the environment are exploited and reflected in our regret bounds. The constraints handle general dependencies between losses (even across time), and are flexible enough to also account for a loss budget, which the environment is not allowed to exceed. The performance of the resulting algorithms is highlighted in two numerical examples, which include a nonlinear and online system identification task.
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11:40-12:00, Paper WeA05.6 | |
Stability and Robustness of Distributed Suboptimal Model Predictive Control (I) |
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Belgioioso, Giuseppe | ETH Zürich |
Liao-McPherson, Dominic | The University of British Columbia |
Hudoba de Badyn, Mathias | ETH Zurich |
Pelzmann, Nicolas | ETH Zurich |
Lygeros, John | ETH Zurich |
Dorfler, Florian | Swiss Federal Institute of Technology (ETH) Zurich |
Keywords: Predictive control, Decentralized control, Networked systems
Abstract: In distributed model predictive control (MPC), the control input at each sampling time is computed by solving a large-scale optimal control problem (OCP) over a finite horizon using distributed algorithms. Typically, such algorithms require several (virtually, infinite) communication rounds between the subsystems to converge, which is a major drawback both computationally and from an energetic perspective (for wireless systems). Motivated by these challenges, we propose a suboptimal distributed MPC scheme in which the total communication burden is distributed also in time, by maintaining a running solution estimate for the large-scale OCP and updating it at each sampling time. We demonstrate that, under some regularity conditions, the resulting time-distributed suboptimal MPC control law recovers the qualitative robust stability properties of optimal MPC, if the communication budget at each sampling time is large enough.
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WeA06 |
Room 311 |
Nonlinear System Identification I |
Regular Session |
Chair: Ushirobira, Rosane | Inria |
Co-Chair: Lataire, John | Vrije Universiteit Brussel |
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10:00-10:20, Paper WeA06.1 | |
Constructing Annihilators for Parameter Estimation in Nonlinearly Parameterized Signals |
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Ushirobira, Rosane | Inria |
Efimov, Denis | Inria |
Keywords: Continuous time system estimation, Nonlinear system identification
Abstract: This paper studies the theoretical challenge of linearly representing a class of nonlinearly parameterized estimation problems. Conventional linear regression estimation methods can then be used. For illustration purposes, in our work, the DREM method is chosen to estimate the frequencies for a multi-sinusoidal uncertain signal in a fixed time. Identifying annihilators for signals generated by exponential polynomials with unknown parameters is the first step to accomplishing the linear representation. The annihilators are obtained as time-delay operators constructed with an Ore extension. The fundamental idea is to use the action of these operators on exponential polynomials to obtain the linear regression in nonlinear unknown quantities. We precisely characterize the annihilator as a principal ideal using appropriate Ore extensions, substantially simplifying further calculations. Some examples illustrate our annihilator’s design.
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10:20-10:40, Paper WeA06.2 | |
Kernel-Based Identification of Incrementally Input-To-State Stable Nonlinear Systems |
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Scandella, Matteo | Imperial College London |
Bin, Michelangelo | University of Bologna |
Parisini, Thomas | Imperial College & Univ. of Trieste |
Keywords: Nonlinear system identification, Nonparametric methods, Bayesian methods
Abstract: System identification methods based on Reproducing Kernel Hilbert Spaces (RKHS) have proven to be a valuable tool for the identification of linear time-invariant systems in both discrete- and continuous-time. In particular, unlike most other methods, they enable to systematically confer a priori desirable properties, such as stability, on the estimated models. However, existing RKHS methods mainly target impulse responses and, hence, do not extend well to the nonlinear systems' context. In this work, we propose a novel RKHS-based methodology for the identification of discrete-time nonlinear systems guaranteeing that the identified system is incrementally input-to-state stable (δISS). We model the identified system using a predictor function that, given past input and output samples, yields the output prediction at the next time instant. The predictor is selected from an RKHS using a constrained optimization problem that guarantees its δISS properties. The proposed approach is validated via numerical simulations.
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10:40-11:00, Paper WeA06.3 | |
Modeling of Nonlinear Control System with Prior Knowledges Based on Koopman Operator |
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Iwanaga, Yoshihiro | Yokohama National University |
Fujimoto, Yasutaka | Yokohama National Univ |
Keywords: Nonlinear system identification, Data-driven control
Abstract: Recently, extended dynamic mode decomposition (EDMD) has become a popular tool for system identification. The EDMD is a data-driven algorithm to identify a linear or bilinear predictor of the nonlinear system based on the Koopman operator. Although linear and bilinear models are suitable for real-time control, these models' prediction accuracy may not be sufficient for problems such as trajectory planning that require long-term prediction. To address this issue, we introduced the nonlinear predictor obtained from a block matrix representation of the bilinear predictor and compared it with the bilinear model. Furthermore, identifying a physically reasonable predictor from the limited number of noisy experimental data is also a challenging problem. In this study, we utilized several simple prior knowledges to achieve stability and sparsity and to identify the model that has correct dependencies between state and control input. We identified the forklift dynamics from experimental data and showed that the obtained model has high prediction accuracy and is suitable for optimal trajectory planning.
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11:00-11:20, Paper WeA06.4 | |
Identification of Nonlinear Systems Via LPV Model Identification Around a Time-Varying Trajectory |
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Ebrahimkhani, Sadegh | Vrije Universiteit Brussel |
Lataire, John | Vrije Universiteit Brussel |
Keywords: Nonlinear system identification, LPV system identification, Frequency domain identification
Abstract: Nonlinear (NL) systems are appearing in all engineering applications. Deriving models for these systems is important for instance for prediction and control. The goal of this paper is to estimate models of a class of NL systems via linearization around a time-varying setpoint. By considering one stable trajectory of the NL system, the system can be approximated by a linear parameter-varying (LPV) model around this trajectory. Indeed, this LPV model is the NL system linearized around the trajectory, which we will identify by perturbing the trajectory. After the identification of the LPV model, we reconstruct the NL system by symbolic integration of the estimated LPV coefficients. In this paper, we show that to guarantee the integrability of the LPV coefficients, the parametrization of this LPV model must have a specific structure which we will exploit for its identification. This structure shows that the parameter-varying (PV) coefficients of this LPV are related to each other. Finally, simulation results demonstrate the effectiveness of the proposed identification approach.
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11:20-11:40, Paper WeA06.5 | |
Initialization Approach for Nonlinear State-Space Identification Via the Subspace Encoder Approach |
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Ramkannan, Rishi | Eindhoven University of Technology |
Beintema, Gerben Izaak | Eindhoven University of Technology |
Tóth, Roland | Eindhoven University of Technology |
Schoukens, Maarten | Eindhoven University of Technology |
Keywords: Nonlinear system identification, Machine learning
Abstract: The SUBNET neural network architecture has been developed to identify nonlinear state-space models from input-output data. To achieve this, it combines the rolled-out nonlinear state-space equations and a state encoder function, both parameterised as neural networks The encoder function is introduced to reconstruct the current state from past input-output data. Hence, it enables the forward simulation of the rolled-out state-space model. While this approach has shown to provide high-accuracy and consistent model estimation, its convergence can be significantly improved by efficient initialization of the training process. This paper focuses on such an initialisation of the subspace encoder approach using the Best Linear Approximation (BLA). Using the BLA provided state-space matrices and its associated reconstructability map, both the state-transition part of the network and the encoder are initialized. The performance of the improved initialisation scheme is evaluated on a Wiener-Hammerstein simulation example and a benchmark dataset. The results show that for a weakly nonlinear system, the proposed initialisation based on the linear reconstructability map results in a faster convergence and a better model quality.
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11:40-12:00, Paper WeA06.6 | |
Physics-Informed Learning Using Hamiltonian Neural Networks with Output Error Noise Models |
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Moradi, Sarvin | Eindhoven University of Technology |
Jaensson, Nick | Eindhoven University of Technology |
Tóth, Roland | Eindhoven University of Technology |
Schoukens, Maarten | Eindhoven University of Technology |
Keywords: Nonlinear system identification, Machine learning
Abstract: In order to make data-driven models of physical systems interpretable and reliable, it is essential to include prior physical knowledge in the modeling framework. Hamiltonian Neural Networks (HNNs) implement Hamiltonian theory in deep learning and form a comprehensive framework for modeling autonomous energy-conservative systems. Despite being suitable to estimate a wide range of physical system behavior from data, classical HNNs are restricted to systems without inputs and require noiseless state measurements and information on the derivative of the state to be available. To address these challenges, this paper introduces an Output Error Hamiltonian Neural Network (OE-HNN) modeling approach to address the modeling of physical systems with inputs and noisy state measurements. Furthermore, it does not require the state derivatives to be known. Instead, the OE-HNN utilizes an ODE-solver embedded in the training process, which enables the OE-HNN to learn the dynamics from noisy state measurements. In addition, extending HNNs based on the generalized Hamiltonian theory enables to include external inputs into the framework which are important for engineering applications. We demonstrate via simulation examples that the proposed OE-HNNs results in superior modeling performance compared to classical HNNs.
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WeA07 |
Room 312 |
Identification, Learning and Control of Quantum Systems I |
Open Invited Session |
Chair: Petersen, Ian R | The Australian National University |
Co-Chair: Ohki, Kentaro | Kyoto University |
Organizer: Dong, Daoyi | University of New South Wales |
Organizer: Li, Jr-Shin | Washington University in St. Louis |
Organizer: Qi, Bo | Chinese Academy of Scineces |
Organizer: Petersen, Ian R | The Australian National University |
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10:00-10:20, Paper WeA07.1 | |
Coherent Quantum LQG Controllers with Luenberger Dynamics (I) |
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Vladimirov, Igor | Australian National University |
Petersen, Ian R | The Australian National University |
Keywords: Stochastic control, Synthesis of stochastic systems, Control under computation constraints
Abstract: This paper is concerned with the coherent quantum linear-quadratic-Gaussian control problem of minimising an infinite-horizon mean square cost for a measurement-free field-mediated interconnection of a quantum plant with a stabilising quantum controller. The plant and the controller are multimode open quantum harmonic oscillators, governed by linear quantum stochastic differential equations and coupled to each other and the external multichannel bosonic fields in the vacuum state. We discuss an interplay between the quantum physical realizability conditions and the Luenberger structure associated with the classical separation principle. This leads to a quadratic constraint on the controller gain matrices, which is formulated in the framework of a swapping transformation for the conjugate positions and momenta in the canonical representation of the controller variables. For the class of coherent quantum controllers with the Luenberger dynamics, we obtain first-order necessary conditions of optimality in the form of algebraic equations, involving a matrix-valued Lagrange multiplier.
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10:20-10:40, Paper WeA07.2 | |
Correlation Functions for Realistic Continuous Quantum Measurement (I) |
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Guilmin, Pierre | Alice & Bob, Mines Paris |
Rouchon, Pierre | PSL Université |
Tilloy, Antoine | Mines Paris |
Keywords: Estimation and filtering
Abstract: We propose a self-contained and accessible derivation of an exact formula for the n-point correlation functions of the signal measured when continuously observing a quantum system. The expression depends on the initial quantum state and on the Stochastic Master Equation (SME) governing the dynamics. This derivation applies to both jump and diffusive evolutions and takes into account common imperfections of realistic measurement devices. We show how these correlations can be efficiently computed numerically for commonly filtered and integrated signals available in practice.
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10:40-11:00, Paper WeA07.3 | |
Measurement-Based Control for Minimizing Energy Functions in Quantum Systems (I) |
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Clausen, Henrik Glavind | Aalborg University |
Abdul Rahman, Salahuddin | Aalborg University |
Karabacak, Ozkan | Aalborg University |
Wisniewski, Rafal | Aalborg University |
Keywords: Stochastic control, Synthesis of stochastic systems, Identification for control
Abstract: In variational quantum algorithms (VQAs), the most common objective is to find the minimum energy eigenstate of a given energy Hamiltonian. In this paper, we consider the general problem of finding a sufficient control Hamiltonian structure that, under a given feedback control law, ensures convergence to the minimum energy eigenstate of a given energy function. By including quantum non-demolition (QND) measurements in the loop, convergence to a pure state can be ensured from an arbitrary mixed initial state. Based on existing results on strict control Lyapunov functions, we formulate a semidefinite optimization problem, whose solution defines a non-unique control Hamiltonian, which is sufficient to ensure almost sure convergence to the minimum energy eigenstate under the given feedback law and the action of QND measurements. A numerical example is provided to showcase the proposed methodology.
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11:00-11:20, Paper WeA07.4 | |
Analysis of Non-Markovian Passive Quantum Linear Systems' Response to Single-Photon Input Fields (I) |
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Sun, Zheng-Yi | Shanghai Jiao Tong University |
Xue, Shibei | Shanghai Jiao Tong University |
Miao, Zibo | Harbin Institute of Technology, Shenzhen |
Dong, Zhiyuan | Harbin Institute of Technology (Shenzhen) |
Li, Dewei | Shanghai Jiao Tong University |
Pan, Lulu | Shanghai Jiao Tong University |
Jiang, Min | Soochow University |
Keywords: Stochastic control, Realization theory, Complex system management
Abstract: In this paper, we analyze the response of passive quantum linear systems in a non-Markovian environment to single photon input fields. Based on an augmented modelling method for non-Markovian quantum systems, analytic forms of output intensity and output covariance function in steady-state are derived. These results allow us to quantitatively analyze the influence of non-Markovian environment on system response under a framework of linear system theory.
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11:20-11:40, Paper WeA07.5 | |
Probabilistic Bounds with Quadratic-Exponential Moments for Quantum Stochastic Systems (I) |
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Vladimirov, Igor | Australian National University |
Keywords: Stochastic control, Synthesis of stochastic systems
Abstract: This paper is concerned with quadratic-exponential moments (QEMs) for dynamic variables of quantum stochastic systems with position-momentum type canonical commutation relations. The QEMs play an important role for statistical ``localisation'' of the quantum dynamics in the form of upper bounds on the tail probability distribution for a positive definite quadratic function of the system variables. We employ a randomised representation of the QEMs in terms of the moment-generating function (MGF) of the system variables, which is averaged over its parameters using an auxiliary classical Gaussian random vector. This representation is combined with a family of weighted L^2-norms of the MGF, leading to upper bounds for the QEMs of the system variables. These bounds are demonstrated for open quantum harmonic oscillators with vacuum input fields and non-Gaussian initial states.
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WeA08 |
Room 313 |
Distributed Optimization for Large-Scale Systems I |
Regular Session |
Chair: Oliva, Gabriele | University Campus Bio-Medico of Rome |
Co-Chair: Cheng, Songsong | Anhui University |
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10:00-10:20, Paper WeA08.1 | |
Distributed Low-Effort Load Balancing in the Presence of Time-Delays |
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Charalambous, Themistoklis | University of Cyprus |
Panzieri, Stefano | Universitá Di Roma Tre |
Oliva, Gabriele | University Campus Bio-Medico of Rome |
Keywords: Distributed optimization for large-scale systems, Multi-agent systems, Graph-based methods for networked systems
Abstract: In this paper, we investigate the problem of distributed load balancing under network capacity constraints, where the participating agents cooperate with the aim of jointly minimizing both the workload disparity among them as well as the overall workload transfer. Classical approaches for asymptotic convergence to the global optimum in a distributed fashion typically assume timely exchange of information between neighboring agents of a given multi-agent system. This assumption is not necessarily valid in practical settings due to non-commensurate (heterogeneous) communication and processing delays that might affect transmissions at different times. More specifically, we consider what effect multiple heterogeneous time-varying delays, among the agents can have on the distributed load balancing problem. We show that the distributed load balancing problem under bounded heterogeneous time-varying delays is globally asymptotically stable, but the rate of convergence is affected. Bounds on the convergence rate are provided with respect to an upper bound on the delays. Simulation examples are provided to show the validity and performance of our theoretical results.
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10:20-10:40, Paper WeA08.2 | |
Zeroth-Order Gradient Tracking for Distributed Constrained Optimization |
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Cheng, Songsong | Anhui University |
Yu, Xin | Anhui University |
Fan, Yuan | Anhui University |
Xiao, Gaoxi | Nanyang Technological University |
Keywords: Distributed optimization for large-scale systems, Multi-agent systems, Consensus
Abstract: Distributed optimization is an important and practical problem that arose from machine learning, smart grid, and multi-robot systems. In this paper, we propose a zeroth-order gradient tracking method to solve a class of constrained distributed optimization problems with nonidentical feasible sets. We design a more general pseudo-gradient estimation scheme, which includes the existing coordinate descent, discretized gradient descent, and spherical smoothing methods as its special cases. Moreover, we propose pseudo-gradient tracking with projection dynamics to deal with nonidentical feasible set constraints and achieve the optimal solution. We show the proposed algorithm achieves the optimal solution with an O(ln T/√T) convergence rate. Finally, we present an example to demonstrate the effectiveness of the proposed algorithm
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10:40-11:00, Paper WeA08.3 | |
A Totally Asynchronous Algorithm for Time-Varying Optimization Problems |
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Behrendt, Gabriel | University of Florida |
Hale, Matthew | University of Florida |
Keywords: Distributed optimization for large-scale systems, Convex optimization, Multi-agent systems
Abstract: This paper presents a decentralized algorithm for a team of agents to track time-varying fixed points that are the solutions to time-varying convex optimization problems. The algorithm is first-order, and it allows for total asynchrony, i.e., all communications and computations can occur with arbitrary timing and arbitrary (finite) delays. Convergence rates are computed in terms of the communications and computations that agents execute, without specifying when they must occur. These rates apply to convergence to the minimum of each individual objective function, as well as agents’ long-run behavior as their objective functions change. Then, to improve the usage of limited communication and computation resources, we optimize the timing of agents’ operations relative to changes in their objective functions to minimize fixed point tracking error over time. Simulation results illustrate these developments.
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11:00-11:20, Paper WeA08.4 | |
Rate Analysis of Dual Averaging for Nonconvex Distributed Optimization |
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Liu, Changxin | KTH Royal Institute of Technology |
Wu, Xuyang | KTH Royal Institute of Technology |
Yi, Xinlei | KTH Royal Institute of Technology |
Shi, Yang | University of Victoria |
Johansson, Karl H. | KTH Royal Institute of Technology |
Keywords: Distributed optimization for large-scale systems, Multi-agent systems, Consensus
Abstract: This work studies nonconvex distributed constrained optimization over stochastic communication networks. We revisit the distributed dual averaging algorithm, which is known to converge for convex problems. We start from the centralized case, for which the change of two consecutive updates is taken as the suboptimality measure. We validate the use of such a measure by showing that it is closely related to stationarity. This equips us with a handle to study the convergence of dual averaging in nonconvex optimization. We prove that the squared norm of this suboptimality measure converges at rate mathcal{O}(1/t). Then, for the distributed setup we show convergence to the stationary point at rate mathcal{O}(1/t). Finally, a numerical example is given to illustrate our theoretical results.
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11:20-11:40, Paper WeA08.5 | |
Distributed Event-Triggered Nash Equilibrium Seeking for Noncooperative Games on Unbalanced Digraphs |
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Cai, Xin | Xinjiang University |
Keywords: Distributed optimization for large-scale systems, Event-triggered and self-triggered control, Multi-agent systems
Abstract: This paper addresses a Nash equilibrium (NE) seeking problem for noncooperative games with double-integrator agents who communicate with each other on an unbalanced directed graph. To deal with the unbalance in the consensus term, an auxiliary variable is introduced in the designed distributed NE seeking algorithm and is the estimation of the left eigenvector of the Laplacian matrix associated with the zero eigenvalue. Moreover, an event-triggered broadcasting scheme is proposed to reduce communication loads in the network. It is shown that the proposed communication scheme is free of the Zeno behavior and the asymptotic convergence of the designed algorithm is obtained. Simulation results are demonstrated to validate the proposed methods.
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11:40-12:00, Paper WeA08.6 | |
Revisiting the Curvature-Aided IAG: Improved Theory and Reduced Complexity |
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Berglund, Erik | KTH Royal Institute of Technology |
Khirirat, Sarit | Mohamed Bin Zayed University of Artificial Intelligence |
Wu, Xuyang | KTH Royal Institute of Technology |
Magnusson, Sindri | Stockholm University |
Johansson, Mikael | Royal Institute of Technology |
Keywords: Distributed optimization for large-scale systems, Convex optimization
Abstract: The curvature-aided IAG (CIAG) algorithm is an efficient asynchronous optimization method that accelerates IAG using a delay compensation technique. However, existing step-size rules of CIAG are conservative and hard to implement, and the Hessian computation in CIAG is often computationally expensive. To alleviate these issues, we first provide an easy-to-implement and less conservative step-size rule for CIAG. Next, we propose a modified CIAG algorithm that reduces the computational complexity by approximating the Hessian with constant matrices. Convergence results are derived for each algorithm on both convex and strongly convex problems. Numerical experiments on logistic regression demonstrate their effectiveness.
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WeA09 |
Room 314 |
Co-Creative Cyber Physical System in Smart Manufacturing and Logistics I |
Open Invited Session |
Chair: Kaihara, Toshiya | Kobe University |
Co-Chair: Nishi, Tatsushi | Okayama University |
Organizer: Kaihara, Toshiya | Kobe University |
Organizer: Nishi, Tatsushi | Okayama University |
Organizer: Nonaka, Youichi | Hitachi, Ltd |
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10:00-10:20, Paper WeA09.1 | |
A Study on Collaborative Logistics Network Design with Truck Sharing under Demand Uncertainty (I) |
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Ito, Asumi | Kobe University |
Kaihara, Toshiya | Kobe University |
Kokuryo, Daisuke | Kobe University |
Fujii, Nobutada | Kobe University |
Keywords: Supply chains and networks, Logistics in manufacturing, Complex logistic systems
Abstract: The sharing economy is a new innovative business model for more flexible and sustainable logistics. This paper proposes a stochastic programming model for supply chain network design with truck sharing. The model considers demand uncertainty and optimizes allocation and operation of trucks. A case study with realistic data is presented by applying the model to a supply chain with different collaboration level. A sensitivity analysis of cost parameter for sharing service is also conducted to evaluate the impact on business sustainability. The results show that higher collaboration level successfully copes with demand uncertainty, and improves revenues in the entire supply chain.
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10:20-10:40, Paper WeA09.2 | |
Case Study of E-PDPTW for Delivery Planning of Electricity and Commodities in Case of Disaster (I) |
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Miyamoto, Toshiyuki | Osaka Institute of Technology |
Hiroshima, Tensei | Osaka University |
Kitamura, Shoichi | Mitsubishi Electric Corporation |
Naito, Kento | Mitsubishi Electric |
Mori, Kazuyuki | Mitsubishi Electric Corporation |
Keywords: Logistics in manufacturing, Operations research, Supply chains and networks
Abstract: Resilience refers to the ability to cope with various external risks and shocks; the concept of disaster resilience is an important issue in Japan, where there are many natural disasters. We consider a situation where a large-scale power outage occurred due to a disaster; electrical vehicles (EVs) are used to deliver both of electricity and commodities. In our previous study, we formulated the Electric Vehicle Pickup and Delivery Problem with Time Window (E-PDPTW) for delivery planning of them as a mixed integer programming problem, and we proposed a heuristic method to find feasible solutions in realistic computation time. In this paper, we conduct a case study of the proposed method using realistic data.
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10:40-11:00, Paper WeA09.3 | |
Sim2Real Grasp Pose Estimation for Adaptive Robotic Applications (I) |
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Horváth, Dániel | Institute for Computer Science and Control (SZTAKI) and Eötvös L |
Bocsi, Kristóf | SZTAKI |
Erdos, Gabor | SZTAKI |
Istenes, Zoltán | Eötvös Loránd University |
Keywords: Smart manufacturing, Cyber-physical production systems
Abstract: Adaptive robotics plays an essential role in achieving truly co-creative cyber physical systems. In robotic manipulation tasks, one of the biggest challenges is to estimate the pose of given workpieces. Even though the recent deep-learning-based models show promising results, they require an immense dataset for training. In this paper, two vision-based, multi-object grasp pose estimation models (MOGPE), the MOGPE Real-Time and the MOGPE High-Precision are proposed. Furthermore, a sim2real method based on domain randomization to diminish the reality gap and overcome the data shortage. Our methods yielded an 80% and a 96.67% success rate in a real-world robotic pick-and-place experiment, with the MOGPE Real-Time and the MOGPE High-Precision model respectively. Our framework provides an industrial tool for fast data generation and model training and requires minimal domain-specific data.
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11:00-11:20, Paper WeA09.4 | |
Multi-Arm Motion-Generating Method Based on Each Robot Movement Vector in Time Slice (I) |
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Hayashi, Naohiro | Hitachi, Ltd |
Nakasu, Nobuaki | Hitachi, Ltd |
Keywords: Smart assembly, Assembly and disassembly, Smart manufacturing
Abstract: This paper proposes a multi-arm-motion-generation method. Arm robots are expected to substitute workers, especially since multi-arm flexibly is adaptable to diverse product models. However, due to the complexity of the multi-arm motion, many hours of manual motion teaching are required.Therefore, we developed a multi-arm motion-generating method for automatically generating collision-free multi-arm motions with an equal or faster time than manually teaching motion. Our proposed method is a collision-circumvent and stop-avoidance method that takes into account each robot movement vector in time slices. Experiments were conducted to evaluate the proposed method, and the results indicate that the method can generate a short circumvent avoidance trajectory compared with a conventional collision-avoidance method for avoiding all passing areas of robots.
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11:20-11:40, Paper WeA09.5 | |
Development of a Novel Visual Servoing Probe Test Method for Fault Diagnosis of Printed Circuit Boards (I) |
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Tipary, Bence | SZTAKI |
Juniki, Ádám | SZTAKI |
Erdos, Gabor | SZTAKI |
Takács, Emma | SZTAKI |
Németh, Kornél | University of Pannonia |
Keywords: Flexible and reconfigurable manufacturing systems, Quality assurance and maintenance
Abstract: Printed circuit board (PCB) measurement and repair is a challenging task that requires experience and expertise to perform. PCB diagnosis and repair shops employ skilled operators to carry out the corresponding measurement tasks using measuring instruments (e.g., oscilloscopes, multimeters) in order to uncover the condition of a particular product. However, these tasks are often repetitive and meticulous, and additionally, the results need to be collected and carefully documented so that the gathered experience regarding the product can be re-used when the next product of the same type arrives into the shop. Nevertheless, the diagnosis of used PCBs is less researched and current flexible automation possibilities are limited. In this paper, a novel visual servoing probe test method and measurement tool are proposed to provide a flexible solution for PCB diagnosis with a higher level of automation. The aim of the approach is to reduce the burden on the operators by carrying out the repetitive measurement tasks and automatically storing the results while leaving the responsibility of measurement profile setup to the human expert. The proposed visual servo system uses manually teached-in measurement points, where template patterns are recorded using cameras, and it is capable of compensating positioning errors in the range of a couple of millimeters. The proof of concept of the proposed method is presented through motherboard measuring experiments, with a 99.7% success rate.
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11:40-12:00, Paper WeA09.6 | |
Robust Optimization Model for Bilevel Production Planning with Customers Uncertainty (I) |
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Nakao, Jun | Okayama University |
Nishi, Tatsushi | Okayama University |
Liu, Ziang | Okayama University |
Keywords: Supply chain management , Production planning and control, Operations research
Abstract: Mass customization is the method for effectively postponing the task of differentiating a product for a specific customer until the latest possible point in the supply chain network. We consider the problem of a production planning with customer preferences. In the module production, products are manufactured by combining modules according to customer preferences. We develop a robust optimization model that considers uncertainties in manufacturer and customer decisions, and cost parameters in the supply chain planning. The proposed model is treated as a Stackelberg model in which the leader first optimizes its own objective function and then followers individually find their optimal solutions under the conditions. The problem is formulated as a bilevel production planning problem in which the manufacturer is a leader and multiple customers are followers. The manufacturer's problem is to maximize profit, and customers' problem is to maximize satisfaction with products which are produced by the manufacturer. The problem is formulated as a single-level mixed integer programming problem by adding constraint equations that guarantees the optimality of the lower-level customer satisfaction maximization problem through strong duality to the upper-level constraint equations. Computational results are provided to show the robustness of the proposed model and its ability to achieve efficient production planning.
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WeA10 |
Room 315 |
Event-Triggered and Self-Triggered Control I |
Open Invited Session |
Chair: Hirche, Sandra | Technical University of Munich |
Co-Chair: Heemels, Maurice | Eindhoven University of Technology |
Organizer: Heemels, Maurice | Eindhoven University of Technology |
Organizer: Hirche, Sandra | Technical University of Munich |
Organizer: Johansson, Karl H. | KTH Royal Institute of Technology |
Organizer: Malisoff, Michael | Louisiana State Univ |
Organizer: Nowzari, Cameron | George Mason University |
Organizer: Postoyan, Romain | CRAN, CNRS, Université De Lorraine |
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10:00-10:20, Paper WeA10.1 | |
Self-Triggered Output Feedback Control for Nonlinear Networked Control Systems Based on Hybrid Lyapunov Functions (I) |
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Hertneck, Michael | University of Stuttgart |
Allgower, Frank | University of Stuttgart |
Keywords: Control of networks, Control under communication constraints, Event-triggered and self-triggered control
Abstract: Most approaches for self-triggered control (STC) of nonlinear networked control systems (NCS) require measurements of the full system state to determine transmission times. However, for most control systems only a lower dimensional output is available. To bridge this gap, we present in this paper an output-feedback STC approach for nonlinear NCS. An asymptotically stable observer is used to reconstruct the plant state and transmission times are determined based on the observer state. The approach employs hybrid Lyapunov functions and a dynamic variable to encode past state information and to maximize the time between transmissions. It is non-conservative in the sense that the assumptions on plant and controller are the same as for dynamic STC based on hybrid Lyapunov functions with full state measurements and any asymptotically stabilizing observer can be used. We conclude that the proposed STC approach guarantees asymptotic stability of the origin for the closed-loop system.
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10:20-10:40, Paper WeA10.2 | |
Deep Learning of a Communication Policy for an Event-Triggered Observer for Linear Systems |
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Marchand, Mathieu | Université Paris-Saclay - ONERA |
Andrieu, Vincent | Université De Lyon |
Bertrand, Sylvain | ONERA |
Janny, Steeven | LIRIS, INSA Lyon |
Piet-Lahanier, Helene | ONERA |
Keywords: Event-triggered and self-triggered control, Observers for linear systems, Learning for control
Abstract: The problem of learning a communication policy is investigated in this paper for the design of an event-triggered observer for discrete-time LTI systems. Firstly, the event-triggered observer problem is formulated as an optimisation problem. The existence of a solution to this problem (communication policy) is investigated and it is verified if this solution still preserves the stability of the estimation error dynamics. Secondly, an algorithm is provided to approximate this optimal solution using neural networks and deep learning. Simulation examples are provided to illustrate the effectiveness of the learned communication policies.
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10:40-11:00, Paper WeA10.3 | |
Event-Triggered Distributed Observer for Rigid Body Systems Over Jointly Connected Acyclic Switching Networks (I) |
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Wang, Tianqi | The Hong Kong Polytechnic University |
Huang, Jie | The Chinese University of Hong Kong |
Keywords: Event-based control, Distributed control and estimation, Consensus
Abstract: A drawback of the existing event-triggered distributed observer for a rigid body leader system over jointly connected switching networks is that the upper bounds of two key design parameters were only shown to exist without giving an explicit estimate of the upper bounds. In this paper, by assuming that the communication network is acyclic, we further show that these two design parameters can take any positive value by choosing other parameters appropriately. We will also apply our event-triggered distributed observer to the leader-following consensus problem of multiple rigid body systems and illustrate our design by a numerical example.
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11:00-11:20, Paper WeA10.4 | |
On the Trade-Off between Event-Based and Periodic State Estimation under Bandwidth Constraints (I) |
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Baumann, Dominik | Aalto University |
Schön, Thomas Bo | Uppsala University |
Keywords: Event-triggered and self-triggered control, Wireless sensing and control systems, Multi-agent systems
Abstract: Event-based methods carefully select when to transmit information to enable high-performance control and estimation over resource-constrained communication networks. However, they come at a cost. For instance, event-based communication induces a higher computational load and increases the complexity of the scheduling problem. Thus, in some cases, allocating available slots to agents periodically in circular order may be superior. In this article, we discuss, for a specific example, when the additional complexity of event-based methods is beneficial. We evaluate our analysis in a synthetical example and on 20 simulated cart-pole systems.
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11:20-11:40, Paper WeA10.5 | |
An Event-Triggered Adaptive Dynamic Programming Method for Large-Scale HVAC Systems |
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Xue, Shan | South China University of Technology |
Chen, Zhiwen | School of Automation, Central South University |
Liu, Derong | Southern University of Science and Technology |
Shang, Chao | Tsinghua University |
Chen, Hongtian | University of Alberta |
Keywords: Event-triggered and self-triggered control, Learning for control
Abstract: In this paper, an event-triggering adaptive dynamic programming (ADP) algorithm is developed for the temperature control of large-scale HVAC systems. First, the dynamic model of the system is established by using the conservation of mass and energy, which involves the dynamics of the fan and the cooling coil. Second, the multi-zone temperature control problem is treated as a non-zero-sum game, which requires solving the coupled Hamilton-Jacobian (HJ) equations. Then, the ADP algorithm is employed to solve the HJ equation. Importantly, in order to reduce the network transmission burden of large-scale HVAC systems, the ADP algorithm developed in this paper is based on event-triggering mechanism. Theoretical analysis proves that the tracking error and the neural network weight estimation error are uniformly ultimately bounded. Simulation results verify the effectiveness of the algorithm.
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11:40-12:00, Paper WeA10.6 | |
Dynamic Water Stress Threshold Determination for Precision Deficit Irrigation Control Using Progressive Clustering Approach |
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Owino, Lina | University of Duisburg-Essen |
Söffker, Dirk | Univ of Duisburg-Essen |
Keywords: Machine learning, Modeling and control of agriculture, Precision agriculture
Abstract: Precision deficit irrigation offers a solution to the increasing global pressure on freshwater resources occasioned by a rising demand for agricultural outputs to support a growing human population. Plant physiological responses to water deficit are describe in terms defining severity of water stress. Implementation of deficit irrigation control strategies capable of achieving the twin goals of maximizing potential yield and minimizing cumulative water consumption requires the identification of water deficit levels corresponding to significant stress thresholds to ensure memory initiation and prevent permanent damage to the crop. In this contribution machine learning approaches are implemented for dynamic identification of water stress thresholds during deficit irrigation of potted maize plants. K-means clustering is initally applied to delineate three zones of water stress described as "no stress", "mild stress" and "high stress" for chronologically segmented data points. Least squares-based polynomial curve fitting is employed to mathematically represent the dynamic progression of stress cluster centroids, with accuracy values ranging between 90 % and 98 %.
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WeA11 |
Room 411 |
Robots Manipulators III |
Regular Session |
Chair: Merzouki, Rochdi | University of Lille/CRIStAL CNRS 9189 |
Co-Chair: Nakashima, Akira | Nanzan University |
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10:00-10:20, Paper WeA11.1 | |
Observability-Based Placement of Inertial Sensors on Robotic Manipulators for Kinematic State Estimation |
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Fennel, Michael | Karlsruhe Institute of Technology |
Driller, Lukas | Karlsruhe Institute of Technology |
Zea, Antonio | Karlsruhe Institute of Technology |
Hanebeck, Uwe | Karlsruhe Institute of Technology (KIT) |
Keywords: Design methodologies, Information and sensor fusion, Robots manipulators
Abstract: In recent years, the demand for accurate and delay-free kinematic state estimates, especially regarding acceleration, led to the adoption of inertial sensors placed along the kinematic chain of robotic manipulators. With state-of-the-art signal processing algorithms, arbitrary setups of accelerometers and gyroscopes can be deployed, raising the question of where and how many sensors should be placed for an optimal estimation quality. This paper presents a novel observability-based approach to answer this question independent of a specific estimator implementation. For this purpose, methods for calculating the required sensor measurement ranges and predicting the estimation quality regarding velocity and acceleration are introduced and discussed. The resulting procedure is validated successfully by comparing predicted and actual estimation quality for two example manipulators, indicating that it can provide meaningful aid to a design engineer.
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10:20-10:40, Paper WeA11.2 | |
Unsupervised Learning-Based Analytical Inverse Kinematics for High-Redundancy Mobile Manipulators |
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Jiokou, Gino | University of Yaoundé 1 |
Melingui, Achille | University of LIlle1 |
Mvogo Ahanda, Joseph Jean-Baptiste | Department of Physics, Faculty of Science, University of Yaounde |
Bouyom Boutchouang, Audrey Hyacinthe | University of Yaounde I |
Lakhal, Othman | University Lille, CRIStAL, CNRS-UMR 9189, |
Merzouki, Rochdi | University of Lille/CRIStAL CNRS 9189 |
Keywords: Modeling, Mobile robots, Robots manipulators
Abstract: Redundant robots manipulator interested the robotics community in the fact that they can perform additional tasks other than the main one. Assembling them on a mobile platform increases the number of degrees of freedom (DOF) and thus allows them to perform more complex tasks in a larger workspace. However, the increase in the number of degrees of freedom further complicates the establishment of the inverse kinematic model. Indeed, for a given End Effector (EE) pose, several configuration joints can be associated. In this paper, the joint parameterisation of the mobile manipulator (MM) is obtained by clustering the workspace and the configuration space. Thus, the robotic system can be reduced to an equivalent non-redundant system, so that existing conventional methods for solving the inverse kinematics (IK) of a non-redundant manipulator can be applied to derive the IK of the system. The proposed approach is validated by conducting a series of simulations
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10:40-11:00, Paper WeA11.3 | |
Observer Based Control for Paddle Juggling with Considering Ball Spin Effect |
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Nakashima, Akira | Nanzan University |
Keywords: Intelligent robotics, Observer design, Control of switched systems
Abstract: This paper deals with the 2-dimensional paddle juggling where a racket hit a ball vertically and iteratively. The racket rebound model is considered where both the translational and rotational velocities of the ball change at the rebound due to the effect of the racket rubber. The LQ servo controller is derived based on the complete ball transition with the racket rebound model. In addition, a whole observer system to estimate all the ball states is proposed which consists of a continuous one for the free flying ball and a discrete one for the ball rebound. Note that it is essential that the rotational velocity can be only estimated by the discrete observer at the rebound. A numerical simulation is performed in order to verify the effectiveness of the total discrete output feedback controller.
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11:00-11:20, Paper WeA11.4 | |
Next Level of Human-Robot Collaboration by Utilizing AI Pose Estimation and Model Predictive Motion Planning Technologies |
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Pozo, Esteban | Hochschule Schmalkalden |
Gerges, Bishoy | University of Twente |
Nafea, Mohammed | Schmalkalden University of Applied Sciences |
Schrödel, Frank | University of Applied Science Schmalkalden |
Keywords: Modeling, Guidance navigation and control, Robots manipulators
Abstract: Over recent years, there has been a significant focus on Human Robot Interaction (HRI). The aim of this interaction is to create a mutually beneficial partnership between humans and robots, with robots contributing precision, speed, and force, while humans provide experience, intuition, and high-level management and control strategy understanding. One of the most crucial factors in achieving a successful HRI is the guidance of these robots. This paper proposes the use of reliable Hand Detection based on Long Short-Term Memory (LSTM) and intelligent robot motion planning based on Model Predictive Control Methods (MPC) to detect hand signals and communicate with the robot. By utilizing vision systems, a micro controller-based Edge AI approach, and a wired connection, the reaction speed of the robot can be optimized to maintain a safe separation distance between the human operator and the robot, thus enabling a collaborative and safe environment. The effectiveness and capabilities of this automation framework are validated through a case study.
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11:20-11:40, Paper WeA11.5 | |
Integration of Robotic Vision and Automatic Tool Changer Based on Sequential Motion Primitive for Performing Assembly Tasks (I) |
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Deng, Zong-Yue | National Taiwan Normal University |
Kang, Li-Wei | National Taiwan Normal University |
Chiang, Hsin-Han | National Taipei University of Technology |
Li, Hsiao-Chi | National Taipei University of Technology |
Keywords: Robots manipulators, Autonomous robotic systems, Mechatronic systems
Abstract: Studies on intelligent robotic manipulation systems have typically focused on the programming efficiency, adaptive control of robotic arms, motion planning of robotic arms, and action diversity of grippers. In this study, a decision tree and visual recognition incorporate into a robotic arm to help it learn complex tasks. This study employed a task tree for the automatic planning of complex tasks, in which a decision-making model was used to generate complex task sets from a pre-built motion dataset in real-time performance. Moreover, the model can analyze the rationality of model steps, introduce new tasks, and perform object analysis. This work applies a support vector machine to identify the state of an object. The model selects a suitable gripper with a rapid gripper switch process by considering the characteristics of the targeting object. This study demonstrated the effectiveness of the proposed approach with suitable intelligence through the assembly task.
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11:40-12:00, Paper WeA11.6 | |
A Comparative Study of Impedance Control for Experimental Hydraulic Arms (I) |
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Arai, Ryo | Shinshu University |
Sakai, Satoru | Shinshu University |
Keywords: Robots manipulators
Abstract: The short paper discusses a comparative study of impedance control for experimental hydraulic arms interacting with humans. There are a lot of impedance controls based on different approaches. However, the existing impedance controls have not been compared. First, we review a nominal model of hydraulic cylinder dynamics and the two existing impedance controls for hydraulic arms. Second, via linearization for the short paper, we propose a comparison method of each impedance control. Third, we numerically compare each impedance control. The effectiveness of the comparison method is confirmed.
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WeA12 |
Room 412 |
Adaptive Control in Mechatronics |
Regular Session |
Chair: Csencsics, Ernst | Vienna University of Technology |
Co-Chair: Ito, Shingo | University of Fukui |
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10:00-10:20, Paper WeA12.1 | |
State Estimation Using Different Disturbance Models for Adaptive Railway Bridges |
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Zeller, Amelie | University of Stuttgart |
Dakova, Spasena | University of Stuttgart |
Stein, Charlotte | University of Stuttgart |
Reksowardojo, Arka P. | École Polytechnique Fédérale De Lausanne |
Senatore, Gennaro | École Polytechnique Fédérale De Lausanne |
Blandini, Lucio | University of Stuttgart |
Böhm, Michael | University of Stuttgart |
Sawodny, Oliver | Univ of Stuttgart |
Tarin, Cristina | University of Stuttgart |
Keywords: Application of mechatronic principles, Smart structures, Parameter and state estimation
Abstract: Adaptive structures are equipped with sensors and actuators to counteract deformations and vibrations caused by external loads. For railway bridges, active control can be used to reduce vibration amplitudes to extend the service life of the structure, thereby increasing resource and emissions efficiency. Model-based control of bridge structures requires knowledge of the structural state and the external disturbance. This paper compares bridge state estimators (Kalman filters), that get no/ full information about the disturbance or include disturbance models of different complexity in the estimation model with respect to the achievable estimation performance. It is shown that the disturbance cannot be neglected, however it is sufficient to take the average train axle weights as average mass (AM)-moving point load (MPL) model into account, while a more complex disturbance model does not improve the estimation performance. Hence, a state and disturbance estimator based on the AM-MPL model is proposed using an Augmented Kalman filter.
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10:20-10:40, Paper WeA12.2 | |
Robust Adaptive Tracking Control of a 3D Vertical Motion System for Nanometer Precision Applications |
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Huaman Loayza, Alex Smith | Technische Universität Ilmenau |
Reger, Johann | TU Ilmenau |
Keywords: Motion control systems, Adaptive control, Disturbance rejection (linear case)
Abstract: In this paper we address the modeling and tracking control problem of an overactuated lift and tilt vertical nanopositioning system. We derive a model based on the rigid body dynamics which adequately describes the first resonance mode of each motion axis. This model is validated with measured data in the frequency domain to illustrate that it adequately reflects the real behavior. We further device an abstract model for the derivation of advanced control strategies. By virtue of the single axis model, three SISO controllers are implemented. The control strategy is accomplished comprising a nominal feedforward and LQG-type controller plus an L1 adaptive augmentation with output feedback. The baseline (or nominal) controller features sufficiently high bandwidth for the mere stabilization, decoupling, and disturbance rejection, while the L1 adaptive component plays a central role for recovering the nominal closed-loop dynamics in the presence of parametric uncertainties w.r.t. the input gain which are quite difficult to handle in the nominal design. The effectiveness and robustness of the proposed control strategy is verified via real-time experiments featuring subnanometer and nanoradian tracking errors which seem to be fully-dominated by the measurement noise.
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10:40-11:00, Paper WeA12.3 | |
Modeling-Free Learning Control of Cross-Coupled Fast Steering Mirror for 2-D Trajectory |
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Ito, Shingo | University of Fukui |
Csencsics, Ernst | Vienna University of Technology |
Schitter, Georg | Vienna University of Technology |
Keywords: Mechatronic systems, Motion control systems
Abstract: This paper proposes modeling-free inversion-based iterative control (MF-IIC) for a fast steering mirror, which is a dual-input dual-output system to generate 2-D optical scanning trajectories. To explicitly compensate for the cross-coupling motions, the MF-IIC iteratively updates the control inputs by learning from the previous trials based on a 2x2 Jacobian matrix. To operate the MF-IIC without system identification in advance, it estimates the Jacobian matrix including the non-diagonal elements for the cross-coupling dynamics simultaneously during learning. For experiments, 19 Hz and 20 Hz sine waves with an amplitude of 0.65 deg. are used for a Lissajous pattern as a reference trajectory. Experimental results show that a tracking error of 320x10^{-3} degrees when feedback control is used for stability. By additionally combing the proposed MF-IIC, the error is decreased by a factor of 68 to 4.64x10^{-3} degrees. It is smaller than MF-IIC without considering the cross coupling explicitly, which achieves a tracking error of 12.1x10^{-3} deg. These two MF-IIC algorithms are also compared by the resulting sampled trajectories in the spatial domain. For that purpose, maximum dead zone diameter is defined as a diameter of the largest circle without sampled points in a scanning area in this paper. While the MF-IIC without considering the cross coupling explicitly for comparison creates a Lissajous pattern with a maximum dead zone diameter of 74.8x10^{-3} degrees, the proposed MF-IIC achieves a Lissajous pattern with a smaller maximum dead zone diameter of 72.9x10^{-3} degrees, demonstrating its effectiveness for high-quality scanning trajectories.
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11:00-11:20, Paper WeA12.4 | |
Pressure Sensor Fault Diagnosis by Using Adaptive Robust Observers |
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Yang, Chengzhi | Zhejiang University |
Zhou, Yong | Zhejiang University |
Chen, Zheng | Zhejiang University |
Zhang, Junhui | Zhejiang University |
Yao, Bin | Purdue University |
Keywords: Mechatronics, Mechatronic systems
Abstract: The model uncertaint of hydraulic systems is a key issue in observer-based fault diagnosis. In this research, for diagnosing pressure sensor faults in hydraulic systems, we present the application of adaptive robust observers design. For reducing model uncertainty and increasing the feasibility of the fault diagnosis scheme, this paper uses a robust filter and controlled parameter adaption to deal with model uncertainty. Then, according to the fault system model, the fault magnitude of the pressure sensor fault is estimated and the residual variance can be generated for diagnosing the sensor fault. By experiments, the fault diagnosis scheme is proven efficient, which is based on adaptive robust observers. Then, the fault magnitude can be estimated.
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11:20-11:40, Paper WeA12.5 | |
Model-Based Flux Control of an Electropermanent Magnet for Adaptive Zero Power Gravity Compensation |
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Pechhacker, Alexander | TU Wien |
Wertjanz, Daniel | TU Wien |
Csencsics, Ernst | Vienna University of Technology |
Schitter, Georg | Vienna University of Technology |
Keywords: Mechatronics, Identification and control methods
Abstract: This paper presents a model-based flux control for a variable reluctance actuator with an electropermanent magnet, used for adaptive zero power gravity compensation in magnetic levitation systems. With the hysteresis of the electropermanent magnet being identified and approximated, tailored current pulses are applied by the model-based flux control to tune the magnetization of the electropermanent magnet. In this way, the resulting stationary reluctance force compensates the gravitational force of the levitated mover mass. Based on the identified hysteresis, a non-linear control law is derived, which is extended by an integrator term to compensate modelling uncertainties. In comparison to the state of the art model-free control, the model-based control increases the force tuning rate by a factor of 14 to 19 N/s and improves the robustness of the experimental system in variable mover positions.
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11:40-12:00, Paper WeA12.6 | |
Run-To-Run Adaptive Nonlinear Feedforward Control of Electromechanical Switching Devices |
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Moya-Lasheras, Eduardo | Universidad De Zaragoza |
Ramirez-Laboreo, Edgar | Universidad De Zaragoza |
Serrano-Seco, Eloy | Universidad De Zaragoza |
Keywords: Motion control systems, Mechatronic systems, Nonlinear adaptive control
Abstract: Feedforward control can greatly improve the response time and control accuracy of any mechatronic system. However, in order to compensate for the effects of modeling errors or disturbances, it is imperative that this type of control works in conjunction with some form of feedback. In this paper, we present a new adaptive feedforward control scheme for electromechanical systems in which real-time measurements or estimates of the position and its derivatives are not technically or economically feasible. This is the case, for example, of commercial electromechanical switching devices such as solenoid actuators. Our proposal consists of two blocks: on the one hand, a feedforward controller based on differential flatness theory; on the other, an iterative adaptation law that exploits the repetitive operation of these devices to modify the controller parameters cycle by cycle. As shown, this law can be fed with any available measurement of the system, with the only requirement that it can be processed and converted into an indicator of the performance of any given operation. Simulated and experimental results show that our proposal is effective in dealing with a long-standing control problem in electromechanics: the soft-landing control of electromechanical switching devices.
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WeA14 |
Room 414 |
Production Planning and Control |
Regular Session |
Chair: Ruskowski, Martin | German Research Center for Artificial Intelligence |
Co-Chair: Andres, Frederic Henri Nicolas | National Institute for Informatics |
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10:00-10:20, Paper WeA14.1 | |
Event-Triggered Hybrid Energy-Aware Scheduling in Manufacturing |
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Shao, Zhean | University of Melbourne |
Li, Wen | University of Melbourne |
Tan, Ying | The Univ of Melbourne |
Keywords: Production planning and control, Sustainable Manufacturing, Control of renewable energy resources
Abstract: Incorporating renewable energy sources (RESs) into manufacturing systems has been an active research area in order to address many challenges originating from the unpredictable nature of RESs such as photovoltaics. In the energy-aware scheduling for manufacturing systems, the traditional off-line scheduling techniques cannot always work well due to their lack of robustness with respect to uncertainties coming from imprecise models or unexpected situations. On the other hand, on-line scheduling or rescheduling, which can improve the robustness by using the model and the latest measurements simultaneously, suffer from a high computational cost. This work proposes a hybrid scheduling framework, which combines the advantages of both off-line scheduling and on-line scheduling, to provide a balanced solution between robustness and computational cost. A novel concept of partially-dispatchable state is introduced. It can be treated as a constant in scheduling when the model works well. When the model does not work well, it is triggered as the variable to tune to improve the performance. Such an event-triggered structure can reduce the number of rescheduling and computational costs while achieving a reasonable performance and enhancing system robustness. Moreover, the choice of partiallydispatchable state also provides an extra design freedom in achieving green manufacturing. Simulation examples on a manufacturing system, which consists of a 100-kW solar photovoltaic system, a 10-machine flow shop production line, a 50-kWh energy storage system, a 100-kW gas turbine, and the grid for power supply, demonstrate the validity and applicability of this event-triggered hybrid scheduling (ETHS) framework.
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10:20-10:40, Paper WeA14.2 | |
Energy-Oriented Crane Scheduling in Steel Coil Storages: Evaluation of Heuristic Approaches |
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Oetjegerdes, Patrick | TU Braunschweig |
Schwier, Patrick | TU Braunschweig |
Weckenborg, Christian | TU Braunschweig |
Spengler, Thomas S. | TU Braunschweig |
Keywords: Job and activity scheduling, Production planning and control, Logistics in manufacturing
Abstract: Steel production is an energy-intense industry. Besides the production process itself, accompanying logistic processes are characterized by a high energy demand due to the weight of the products. We consider a steel coil storage, where a gantry crane stores and retrieves steel coils of up to 35 tons. An energy-oriented approach for the scheduling of crane operations can help save energy and lower operational costs. In industrial settings, crane operators require swift assistance in sequencing crane operations and assigning storage places for the coils. Therefore, we develop different heuristic approaches for the energy-oriented crane scheduling problem and compare them based on a case study derived from a German steel manufacturer.
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10:40-11:00, Paper WeA14.3 | |
Job Scheduling for a Multi-Line Steel Hot Rolling Mill with Selectable Furnaces |
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Kowalski, Martin | TU Wien, Automation and Control Institute E376 |
Kugi, Andreas | TU Wien |
Steinboeck, Andreas | TU Wien |
Keywords: Job and activity scheduling, Production planning and control, Discrete event systems in manufacturing
Abstract: In a steel hot rolling mill, jobs are scheduled in groups for the production at two different production lines. The process of scheduling involves the selection and the sequencing of jobs as well as the assignment of selectable furnaces to some jobs. An optimal schedule minimizes unproductive times during the production while utilizing necessary retoolings of one production line as best as possible for the production at the other line. The resulting optimization problem is similar to a combination of several traveling salesman problems and orienteering problems. A method is presented to accurately model the alternating production process on both lines, including sequence-dependent setup times, production line retoolings, and the use of an induction furnace with three chambers. Based on this model, unproductive times occurring in a given schedule can be calculated. These times are minimized by a tailored optimization algorithm, which consists of a simulated annealing metaheuristic followed by a local search. The effective application and benefit of this algorithm are demonstrated in a case study.
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11:00-11:20, Paper WeA14.4 | |
Evolutionary Algorithm-Based Optimal Parametrization of Multi-Objective Mixed-Integer Linear Programming Scheduling Models |
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Yfantis, Vassilios | RPTU Kaiserslautern-Landau |
Babskiy, Alexander | Technische Universität Kaiserslautern |
Dörig, Bastian | Flexis AG |
Winterer, Thorsten Jan | Flexis AG |
Wagner, Achim | German Research Center for Artificial Intelligence |
Ruskowski, Martin | German Research Center for Artificial Intelligence |
Keywords: Operations research, Production planning and control, Smart factory
Abstract: Modern manufacturing systems strive to optimize many different key performance indicators. Additionally, mathematical programming-based scheduling models enable the explicit considerations of constraints. However, due to the ever-increasing demand for customized products it is not guaranteed that all constraints can be met at the same time. An approach to circumvent this problem of infeasibility is to replace the constraints by soft-constraints, i.e., to penalize their violation in the objective function. The presence of multiple competing objectives and soft-constraints gives rise to multi-objective optimization problems, where a decision maker has to weigh and balance the different objectives and soft-constraints according to his/her preferences and priorities. Ideally the values of all objectives and soft-constraints should lie within the same order of magnitude, making it easy to weigh them against each other. However, for heterogeneous objectives and soft-constraints with different scales and units this might be challenging. This paper presents an evolutionary algorithm for the optimal parametrization of multi-objective mixed-integer linear programming-based scheduling models. The goal of the evolutionary algorithm is to compute weights for the different terms of the objective which lead to a balanced influence on the overall objective at the optimum. Furthermore, the algorithm is extended by introducing an a priori weighing of the objectives in the fitness function of the evolutionary algorithm. The method is demonstrated on a scheduling problem in which a given set of orders has to be allocated to machines within a manufacturing environment.
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11:20-11:40, Paper WeA14.5 | |
A Mathematical Model for the Flexible Job Shop Scheduling Problem with Availability Constraints |
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Perroux, Tom | University of Technology of Troyes |
Arbaoui, Taha | ICD-LOSI, University of Technology of Troyes |
Merghem Boulahia, Leila | UTT |
Keywords: Advanced planning and scheduling, Modeling of manufacturing operations, Production planning and control
Abstract: We tackle the Flexible Job Shop Problem (FJSSP) subject to availability constraints due to maintenance tasks on machines. Previous studies explored meta-heuristic methods to address this problem and solved small-sized instances generated from classical FJSSP benchmark. We first introduce a new benchmark, comprising more than 2000 instances, for the problem based on the well-known FJSSP benchmarks. A mixed integer model is then developed to solve this problem. We carry out a computational study on the proposed benchmark and analyze its performances. Results show that our model can solve small and medium size instances efficiently. We also observe important variation in complexity depending on the class of instance which makes the proposed benchmark interesting to evaluate our approach and further improve the solving process in future works.
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11:40-12:00, Paper WeA14.6 | |
An Open-Loop Solution for a Stochastic Problem with Imperfect State Information and Chance-Constraint Adjusted by an Optimal Gain |
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Silva Filho, Oscar Salviano | Pontifícia Universidade Católica De Campinas - PUCCAMP |
Andres, Frederic Henri Nicolas | National Institute for Informatics |
Keywords: Production planning and control, Operations research, Inventory control
Abstract: This study aims to develop an optimal aggregate production planning policy for a reverse logistics system with imperfect state information and chance constraints. The system consists of a forward channel for storing and distributing products and a backward channel for collecting, remanufacturing, or discarding products. The paper presents a chance-constrained linear-quadratic Gaussian optimization model that considers imperfect state information and formulates an equivalent deterministic problem. It also introduces a minimum variance problem to address the uncontrolled variance of the serviceable inventory variable, whose result is an optimal gain to balance the conditional variances of inventory and production over time, making the solution more cost-efficient. The open-loop solution with the minimum variance gain shows its efficiency through a simple example, reducing the total cost of production by controlling the growth of inventory and production variances. Furthermore, this approach offers a practical way for managers to create inventory-production scenarios for decision-making in a reverse logistics system with imperfect state information and chance constraints.
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WeA15 |
Room 415 |
Control of Renewable Energy Resources II |
Regular Session |
Chair: Mulders, Sebastiaan P. | Delft University of Technology |
Co-Chair: Ishizaki, Takayuki | Tokyo Institute of Technology |
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10:00-10:20, Paper WeA15.1 | |
Monotonicity Analysis of the Optimal Operation Schedule Taking into Acount Power Network Structure |
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Kojima, Yuga | Tokyo University of Marine Science and Technology |
Koike, Masakazu | Tokyo University of Marine Science and Technology |
Ishizaki, Takayuki | Tokyo Institute of Technology |
Imura, Jun-ichi | Tokyo Institute of Technology |
Ramdani, Nacim | Université D'Orléans |
Keywords: Control of renewable energy resources, Optimal operation and control of power systems
Abstract: We consider a day-ahead scheduling problem for resources based on photovoltaic (PV) generation and demand profile predictions.Because the predicted profiles contain uncertainty, the set of profiles is represented as a confidence interval.Giving the predicted profile as a confidence interval, we consider the problem of obtaining ranges for the optimal operating profiles of storage batteries and thermal power plants. This corresponds to finding the region of possible solutions for all parameters representing PV/demand predictions. In order to find the exact solution region efficiently, we focus on the monotonicity of the solution. In particular, we aim to clarify what kind of optimization problem possesses monotonicity. As a first step, we have performed monotonicity analysis in various settings so far. In this study, we show that the problem, where the network structure is taken into account, has monotonicity under conditions with a theoretical proof. We also confirm its practical significance with a numerical example.
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10:20-10:40, Paper WeA15.2 | |
A Non-Singular Fast Terminal Sliding Mode Approach to Improve the Network Stability of Wind Rich Power Grids |
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Musarrat, Md Nafiz | University of Louisiana at Lafayette |
Fekih, Afef | Univ of Louisiana at Lafayette |
Md. Rabiul, Islam | University of Wollongong |
Keywords: Control of renewable energy resources, Sliding mode control, Fault-tolerant
Abstract: The increased penetration of wind energy conversion systems into the grid creates many challenges for maintaining grid stability, reliability and efficiency. This paper proposes an approach that integrates the robustness and fast convergence capability of non-singular fast terminal sliding mode control (NFTSMC) with the fast current support of static synchronous compensators (STATCOM) to improve the dynamic stability of wind energy systems during network disturbances. The NFTSMC control approach is designed for the inner current control loop of a STATCOM with voltage source inverter topology. Its main objective is to support both the active and reactive currents and thereby effectively regulate the system’s frequency and bus voltage. The proposed approach was implemented to a WECS-based test microgrid subject to sudden load variations and mismatched disturbances. The obtained results confirmed its effectiveness in properly mitigating dynamic instabilities stemming from grid disturbances and maintaining the voltage and frequency within their rated values. Further comparison between the performance of the proposed NFTSMC and that of a standard SMC approach showed better performance and reduced chattering compared to the standard SMC.
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10:40-11:00, Paper WeA15.3 | |
Temperature Homogenization Control of Parabolic Trough Solar Collector Field |
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Song, Yuhui | Southeast University |
Zhang, Junli | Southeast University |
Li, Yiguo | Southeast University |
Pan, Lei | Southeast University |
Liu, Zhenxiang | Southeast University |
Keywords: Control of renewable energy resources, Modeling and simulation of power systems, Control system design
Abstract: The collector fields of large-scale commercial trough solar power stations often face inhomogeneities in environmental parameters and resistance to flow in the pipe network. Aiming at dealing with the problem of uneven distribution of hydraulic parameters and radiation in large collector fields, this study establishes a heat transfer model and a hydraulic model of the collector field and proposes a control strategy for the heat transfer fluid (HTF) flow in the parabolic trough collector (PTC) loops. Based on the proposed hydraulic model, the loop valve opening is directly calculated and fast control of the loop HTF flow is achieved. Simulation results show that the scheme significantly reduces the differences in HTF temperature at the outlet of the PTC loops.
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11:00-11:20, Paper WeA15.4 | |
Measurement Based Flow Speed Estimation for Tidal Turbine Control |
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Recalde-Camacho, Luis | University of Strathclyde |
Yue, Hong | University of Strathclyde |
Keywords: Control of renewable energy resources, Kalman Filtering, Output feedback control (linear case)
Abstract: This work aims to explore effective online torque estimation techniques for tidal turbine control under varying flow conditions. A modified Kalman filter with adaptive features is developed to estimate hydrodynamic torque from a tidal turbine’s available measurements, based on which a modified Newton-Rapson method is employed to calculate the effective flow speed. The rotor speed reference signal required for tidal turbine control can be produced using the estimated torque and flow speed. The Kalman filter model is constructed using on a low frequency lumped parameter model of a horizontal-axis, fixed-pitch, two-bladed variable speed tidal turbine, established from a fully characterised model of a real turbine. The adaptive feature of the Kalman filter allows the tracking of the spatial-temporal variations of the effective flow speed caused by turbulence. Simulation studies are implemented to test the developed algorithm over the full envelope of the flow speeds
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11:20-11:40, Paper WeA15.5 | |
Sensor Fault-Tolerant Control for Wind Turbines: An Iterative Learning Method |
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Liu, Yichao | Delft University of Technology |
Brandetti, Livia | Delft University of Technology |
Mulders, Sebastiaan P. | Delft University of Technology |
Keywords: Control of renewable energy resources, Parameter estimation based methods for FDI, Fault accommodation and Reconfiguration strategies
Abstract: The combined wind speed estimator and tip speed ratio (WSE-TSR) tracking control scheme is widely used to regulate power production for large-scale modern wind turbines. Although very effective, such an advanced control scheme, based on the prior model information, is highly dependent on external measurements. For partial-load region control, the only external information involved is commonly the measured rotor or generator speed. Inaccuracy in such sole measurement results in an unintended turbine operation and might lead to sub-optimal power production and instability. This paper presents a fault-tolerant control (FTC) method, which aims to eliminate the sensor fault effects for modern wind turbine systems. To fulfil this goal, an iterative learning scheme is proposed to detect and estimate the multiplicative sensor fault, on which an adaptive FTC law is formulated such that the effects of the sensor fault are eliminated. Case studies show that the proposed iterative learning FTC method performs well in detecting, estimating, and accommodating the sensor fault under realistic turbulent wind conditions. The advanced wind turbine controller can maintain its control performance even under faulty conditions, preventing further damage to other turbine components and allowing for continuous power production.
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11:40-12:00, Paper WeA15.6 | |
Nonlinear Data Processing for Modelling and Control of the TCP-100 Solar Thermal Power Plant |
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Juuso, Esko Kalevi | University of Oulu |
Yebra, Luis J. | CIEMAT |
Keywords: Control of renewable energy resources, Modeling and simulation of power systems, Nonlinear process control
Abstract: This paper focuses on the utilization of dynamic simulation models in the planning of experiments for control development. The simulation system is a set of models based on the first principles for system level simulation of the complete new TCP-100 research facility at Plataforma Solar de Almerıa (CIEMAT). This new research facility replaced the 32-year-old ACUREX facility with which so many advances in Automatic Control were reached by the research community. The presented models of the parabolic trough collector field (PTC) will be validated with experimental data and the presented simulations are based on the parameter selection from providers’ data sheets and the engineering design project. All state variables are temperatures and input variables include solar radiation, ambient temperature and several setpoints. Several simulation experiments are planned for typical operation days in which the system is operated passing through different operating modes. The nonlinear scaling approach keeps the algorithms unchanged by focusing on the meanings of the measured variables. Variable specific scaling functions are developed for the state and input variables of the facility system level model extended with several temperature differences. The functions of the irradiance do not change which means that also the indicator of the cloudiness remains the same. The preliminary simulation experiments in a limited set of subsystems will be extended before going to the test campaigns with the new facility.
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WeA16 |
Room 416 |
Recent Advances in Modeling and Control of Networked Energy Systems |
Invited Session |
Chair: Strehle, Felix | Karlsruhe Institute of Technology (KIT) |
Co-Chair: Cucuzzella, Michele | University of Pavia |
Organizer: Strehle, Felix | Karlsruhe Institute of Technology (KIT) |
Organizer: Hohmann, Soeren | KIT |
Organizer: Machado Martinez, Juan Eduardo | University of Groningen |
Organizer: Cucuzzella, Michele | University of Pavia |
Organizer: Scherpen, Jacquelien M.A. | University of Groningen |
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10:00-10:20, Paper WeA16.1 | |
Port-Hamiltonian Modelling for Analysis and Control of Gas Networks (I) |
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Malan, Albertus Johannes | Karlsruhe Institute of Technology (KIT) |
Rausche, Lukas Maximilian | Karlsruhe Institute of Technology (KIT) |
Strehle, Felix | Karlsruhe Institute of Technology (KIT) |
Hohmann, Soeren | KIT |
Keywords: Modeling and simulation of power systems, Smart grids, Control system design
Abstract: In this paper, we present finite-dimensional port-Hamiltonian system (PHS) models of a gas pipeline and a network comprising several pipelines for the purpose of control design and stability analysis. Starting from the partial differential Euler equations describing the dynamical flow of gas in a pipeline, the method of lines is employed to obtain a lumped-parameter model, which simplifies to a nonlinear third-order PHS. Parallels between gas networks and power systems are drawn by showing that the obtained pipeline PHS model has the same pi-representation as electrical transmission lines. Moreover, to assist future control design, additional passivity properties of the pipeline PHS model are analysed and discussed. By comparing the proposed PHS models against other models in a standard simulation, we show that the simplifying assumptions have no material effect on the model fidelity. The proposed pipeline and network models can serve as a basis for passivity-based control and analysis while the power system parallels facilitate the transfer of existing methods.
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10:20-10:40, Paper WeA16.2 | |
Hydraulic Parameter Estimation in District Heating Networks (I) |
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Agner, Felix | Lund University |
Kergus, Pauline | CNRS |
Pates, Richard | Lund University |
Rantzer, Anders | Lund Univ |
Keywords: Modeling and simulation of power systems, Smart grids, System identification and modelling
Abstract: Using hydraulic models in control of district heating networks can increase pumping efficiency and reduce sensitivity to hydraulic bottlenecks. These models are usually white-box, as they are obtained based on full knowledge of the district heating network and its components. This type of model is time-consuming to obtain, and might differ from the actual behavior of the system. In this paper, a method is proposed to obtain a grey-box hydraulic model for tree-shaped district heating systems: hydraulic parameters are estimated based on pressure measurements in only two locations. While previous works only estimate parameters related to pressure losses in pipes, this work also includes customers valves in the grey-box model structure, an important inclusion for control-oriented applications. Finally, a numerical example illustrates the proposed method on a small district heating network, showing its ability to obtain an accurate model on the basis of noisy measurements.
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10:40-11:00, Paper WeA16.3 | |
A Predictive Operation Controller for an Electro-Thermal Microgrid Utilizing Variable Flow Temperatures (I) |
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Rose, Max | Fraunhofer Research Institution for Energy Infrastructures and G |
Hans, Christian Andreas | Technische Universitaet Berlin |
Schiffer, Johannes | Brandenburg University of Technology |
Keywords: Optimal operation and control of power systems
Abstract: We propose an optimal operation controller for an electro-thermal microgrid. Compared to existing work, our approach increases flexibility by operating the thermal network with variable flow temperatures and in that way explicitly exploits its inherent storage capacities. To this end, the microgrid is represented by a multi-layer network composed of an electrical and a thermal layer. We show that the system behavior can be represented by a discrete-time state model derived from DC power flow approximations and 1d Euler equations. Both layers are interconnected via heat pumps. By combining this model with desired operating objectives and constraints, we obtain a constrained convex optimization problem. This is used to derive a model predictive control scheme for the optimal operation of electro-thermal microgrids. The performance of the proposed operation control algorithm is demonstrated in a case study.
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11:00-11:20, Paper WeA16.4 | |
Input and State Constrained Inverse Optimal Control with Application to Power Networks (I) |
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Jouini, Taouba Kaouther | Leibniz Universität Hannover |
Sun, Zhiyong | Eindhoven University of Technology (TU/e) |
Renganathan, Venkatraman | Lund University |
Hagenmeyer, Veit | Karlsruhe Institute of Technology |
Keywords: Optimal operation and control of power systems, Power systems stability
Abstract: We study input and state constrained inverse optimal control problems starting from a stabilizing controller with a control Lyapunov function, where the goal is to make the controller an explicit solution of the resulting constrained optimal control problem. For an appropriate cost design and initial states for which a sublevel set of the Lyapunov function is contained in the state constraint set and the initial input lies on an ellipsoid inside the input constraint set, we show that the stabilizing controller solves the constrained optimal control problem. Compared to the state-of-the-art, we avoid solving nonlinear optimization problems evaluated pointwise, i.e., for every state, or in a repetitive fashion, i.e., at each time step. We apply our theoretical results to study the angular droop control studied in (Jouini et al., 2022) of an inverter-based power network. For this, we accommodate the constraints on the angle and power generation and exemplify our approach through a two-inverter case study.
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11:20-11:40, Paper WeA16.5 | |
A Game-Theoretic Market Mechanism for Procuring Flexibility Services in Distribution Networks under Limited Information Sharing (I) |
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Chen, Xiupeng | University of Groningen |
Shomalzadeh, Koorosh | University of Groningen |
Scherpen, Jacquelien M.A. | University of Groningen |
Monshizadeh, Nima | Universiy of Groningen |
Keywords: Smart grids, Analysis and control in deregulated power systems, Optimal operation and control of power systems
Abstract: We propose a game-theoretic market mechanism for energy balancing in a real-time market and formulate the competition among energy consumers as a Generalized Nash Game (GNG). In this framework, the supply function based bidding method is adopted to mitigate the market power of active energy consumers. Moreover, the physical constraints are incorporated to guarantee the secure operation of the distribution network. To steer consumers to the Generalized Nash Equilibrium (GNE) of this game, existing studies usually require participants to share full or partial private information which may not be appropriate for the practical implementation. In this regard, we design a preconditioned forward-backward based algorithm with provable convergence, by which a market participant only needs to share limited non-private information with others.
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11:40-12:00, Paper WeA16.6 | |
Multi-Stage Energy Management System Based on Stochastic Optimization and Extremum-Seeking Adaptation |
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Gheouany, Saad | ERERA, National School of Arts and Crafts, Mohammed V University |
Ouadi, Hamid | Ismra |
Berrahal, Chaker | LSIB Laboratory, FST Mohammedia, Hassan II University of Casabla |
El Bakali, Saida | ERERA, ENSAM, Mohammed V University, Rabat, Morocco |
El-bakkouri, Jamal | ENSEM of Casablanca, Hassan II University of Casablanca |
Giri, Fouad | University of Caen Normandie |
Keywords: Smart grids, Extremum seeking and model free adaptive control, Real time optimization and control
Abstract: This paper proposes a Multi-stage Home Energy Management System (MS-HEMS) for power demand distribution among the Photovoltaic system (PV), the Energy Storage System (ESS), and the Electrical Power Grid (EPG). MS-HEMS consists of two layers: the Anticipative layer (AL) and the reactive layer (RL). The AL employs Particle Swarm Optimization (PSO) for day-ahead energy management based on weather and energy consumption forecasts; the RL includes an Extremum-Seeking Controller (ESC) that determines the ideal power setpoint of each source in real-time, compensating for prediction uncertainties and calculation time horizons. The optimization problem considers the energy bill, Peak to Average Ratio (PAR), and battery degradation cost. The proposed MS-HEMS is highlighted using predicted and actual measurements and increased the energy bill gain by 10.8% while reducing the PAR by 56.1% compared to the offline approach (OF-HEMS).
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WeA18 |
Room 418 |
Learning for Multi-Robot and Networked Systems |
Open Invited Session |
Chair: Xu, Jun | Harbin Institute of Technology, Shenzhen |
Co-Chair: Busoniu, Lucian | Technical University of Cluj-Napoca |
Organizer: De Schutter, Bart | Delft University of Technology |
Organizer: Busoniu, Lucian | Technical University of Cluj-Napoca |
Organizer: Sosnowski, Stefan | Technical University of Munich (TUM) |
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10:00-10:20, Paper WeA18.1 | |
Adaptive Parameterized Control for Coordinated Traffic Management Using Reinforcement Learning (I) |
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Sun, Dingshan | Delft University of Technology |
Jamshidnejad, Anahita | Delft University of Technology |
De Schutter, Bart | Delft University of Technology |
Keywords: Reinforcement learning and deep learning in control, Machine learning in modelling, prediction, control and automation, Traffic control systems
Abstract: Traffic control is essential to reduce congestion in both urban and freeway traffic networks. These control measures include ramp metering and variable speed limits for freeways, and traffic signal control for urban traffic. However, current traffic control methods are either too simple to respond to complex traffic environment, or too sophisticated for real-life implementation. In this paper, we propose an adaptive parameterized control method for traffic management by using reinforcement learning algorithms. This method takes advantage of the simple structure of parameterized state-feedback controllers for traffic; meanwhile, a reinforcement learning agent is employed to adjust the parameters of the controllers on-line to react to the varying environment. Therefore, the proposed method requires limited real-time computational efforts, and is adaptive to external disturbances. Furthermore, the reinforcement learning agent can coordinate multiple local traffic controllers when adjusting their parameters. The method is validated by a numerical case study on a freeway network. Results show that the proposed method outperforms conventional controllers when the system is exposed to a changing environment.
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10:20-10:40, Paper WeA18.2 | |
Model Predictive Control for Neuromimetic Quantized Systems |
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Sun, Zexin | Boston University |
Baillieul, John | Boston Univ |
Keywords: Neurodynamic optimization and adaptive dynamic programming, Machine learning in modelling, prediction, control and automation, Quantized systems
Abstract: Based on our recent research on neural heuristic quantized systems, we propose an emulation problem consistent with our recently introduced {em neuromimetic} paradigm. This optimal quantization problem can be solved with model predictive control (MPC) by deriving the conditions under which the quantized system can simultaneously guarantee (asymptotic) stability and emulation given dynamical system by optimizing a Lyapunov-like objective function. Taking inspiration from neurobiology, the neuromimetic model features large numbers of discrete inputs that collectively produce stable motions that emulate the behavior of a continuous system. The emulation is produced by solving an optimization problem involving integer variables. The approach in the paper begins by performing the optimization using model predictive control (MPC) and then using a neural network to train a model using the data generated in this process. Complexity is reduced by applying Fincke and Pohst's sphere decoding algorithm to narrow down the search for the optimal solution.
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10:40-11:00, Paper WeA18.3 | |
Optimal Control of Multiple Drones for Obstacle Avoidance (I) |
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Suto, Boglarka | Technical University of Cluj-Napoca |
Codrean, Alexandru | Technical University of Cluj Napoca |
Lendek, Zsofia | Technical University of Cluj-Napoca, VAT RO 22736939 |
Keywords: Multi agent systems, Real-time algorithms, scheduling, and programming
Abstract: The control and path planning of multiple drones in a 3D space with obstacle avoidance is a complex challenge, subject to ongoing research. In this paper we propose an optimal control approach, with a baseline controller and filter running on the drones, and a prediction based optimization algorithm running remotely, as a supervisory controller. The supervisor is responsible for calculating the minimal deviation from the trajectory given by the baseline controllers, such that the obstacle is avoided. The approach is tested in simulations with nonlinear drone models in a realistic setting with noise and transmission delays.
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11:00-11:20, Paper WeA18.4 | |
Adaptive Distributed Formation Control for Multi-Group Large-Scale Multi-Agent Systems: A Hybrid Game Approach (I) |
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Dey, Shawon | University of Nevada, Reno |
Xu, Hao | University of Nevada, Reno |
Fadali, Mohammed Sami | Univ of Nevada |
Keywords: Neurodynamic optimization and adaptive dynamic programming, Reinforcement learning and deep learning in control, Multi agent systems
Abstract: This paper presents a distributed adaptive formation control for large-scale multi-agent systems(LS-MAS) that addresses the ``Curse of Dimensionality". A novel hybrid game theoretic algorithm that effectively integrates the mean field, Stackelberg, and cooperative game seamlessly has been developed. In particular, LS-MAS has been separated into a multiple number of groups, each has one group leader and a significant amount of followers. Next, a cooperative game is utilized for the inter-group formation of leaders, the mean-field game is adopted for intra-group followers, and a Stackelberg game is connecting the leader and followers in same group. A hybrid reinforcement learning algorithm learns the solution of the hybrid game optimal distributed formation. It comprises a multi-actor-critic to obtain the optimal formation control among inter-group leaders in a distributed manner, and a Stackelberg game-based actor-critic-mass algorithm to obtain the followers' adaptive formation control. Lastly, to demonstrate the efficacy of the proposed approaches, numerical simulations have been conducted.
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11:20-11:40, Paper WeA18.5 | |
Cooperative Traffic Signal Control Based on Biased ReLU Neural Network Approximation (I) |
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Luo, Zhiyue | Harbin Institute of Technology, Shenzhen |
Xu, Jun | Harbin Institute of Technology, Shenzhen |
Chen, Fanglin | Harbin Institute of Technology, Shenzhen |
Keywords: Reinforcement learning and deep learning in control, Traffic control systems, Multi agent systems
Abstract: Traffic signal control is important in intelligent transportation system, of which the cooperative control is difficult to realize but yet vital. Popular methods for solving this problem are based on multi-agent reinforcement learning (RL), in which function approximator, e.g., different kinds of neural network play a critical role. In this paper, we propose a multi- agent actor-critic RL framework with global value function and local policy function, for which the piecewise linear neural network, named biased ReLU (BReLU) is used as the function approximator. The reason for doing this is two-fold. First, it has been proved in the control literature that minimizing (maximizing) a piecewise linear function over a polyhedron yields piecewise linear solutions. Second, the BReLU neural network can provide a more accurate approximation than the traditional ReLU neural network when they have similar network structures. The proposed method is evaluated on the Simulation of Urban Mobility (SUMO) environment compared with two benchmark traffic signal control methods. The simulated results illustrate the proposed algorithm can coordinate the signal control between different intersections, achieve lower and more sustainable intersection delays on the whole traffic network.
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11:40-12:00, Paper WeA18.6 | |
Multi-Agent Exploration-Based Search for an Unknown Number of Targets (I) |
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Yousuf, Bilal | Technical University of Cluj-Napoca |
Lendek, Zsofia | Technical University of Cluj-Napoca |
Busoniu, Lucian | Technical University of Cluj-Napoca |
Keywords: Multi agent systems, Data fusion and data mining in control
Abstract: This paper presents an active sensor fusion technique for multiple mobile agents (robots) to detect an unknown number of static targets at unknown positions. To process and fuse sensor measurements from the agents, we use a random finite set formulation with an iterated-corrector probability hypothesis density filter. Our main contribution is to introduce two different multi-agent planners to quickly find the targets. The planners make greedy decisions for the next state of each agent by maximizing an objective function consisting of target refinement and exploration components. We demonstrate the performance of our approach through a series of simulations using homogeneous and heterogeneous agents. The results show that our framework works better than a lawnmower baseline, and that a centralized version of the planner works best.
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WeA19 |
Room 419 |
Data-Based Control I |
Regular Session |
Chair: Zamani, Majid | University of Colorado Boulder |
Co-Chair: You, Keyou | Tsinghua University |
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10:00-10:20, Paper WeA19.1 | |
Moving Horizon Estimation for Digital Twins Using Deep Autoencoders (I) |
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Chakrabarty, Ankush | Mitsubishi Electric Research Laboratories |
P. Vinod, Abraham | Mitsubishi Electric Research Laboratories |
Mansour, Hassan | MERL |
Bortoff, Scott | Merl - Usa |
Laughman, Christopher | Mitsubishi Electric Research Laboratories |
Keywords: Data-based control, Observer design, Nonlinear observers and filter design
Abstract: Digital twins have emerged in recent years as software-based simulation tools that can mirror the behavior of complex dynamical systems. These tools often contain internal representations of a system state that may not be readily available online. In this paper, we develop a data-driven moving horizon estimator for estimating digital twin states only from online measurements. Our framework combines the high expressiveness of deep autoencoders with a moving horizon state estimator that accurately predicts the internal state of the digital twin without complete knowledge of the true system dynamics. We demonstrate that our approach outperforms extended and Koopman Kalman filter solutions on a benchmark reverse van der Pol oscillator example.
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10:20-10:40, Paper WeA19.2 | |
Globally Convergent Policy Gradient Methods for Linear Quadratic Control of Partially Observed Systems |
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Zhao, Feiran | Tsinghua University |
Fu, Xingyun | Tsinghua University |
You, Keyou | Tsinghua University |
Keywords: Data-based control, Output feedback control (linear case), Learning for control
Abstract: While the optimization landscape of policy gradient methods has been recently investigated for partially observed linear systems in terms of both static output feedback and dynamical controllers, they only provide convergence guarantees to stationary points. In this paper, we propose a new policy parameterization for partially observed linear systems, using a past input-output trajectory of finite length as feedback. We show that the solution set to the parameterized optimization problem is a matrix space, which is invariant to similarity transformation. By proving a gradient dominance property, we show the global convergence of policy gradient methods. Moreover, we observe that the gradient is orthogonal to the solution set, revealing an explicit relation between the resulting solution and the initial policy. Finally, we perform simulations to validate our theoretical results.
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10:40-11:00, Paper WeA19.3 | |
Linear Data-Driven Economic MPC with Generalized Terminal Constraint |
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Xie, Yifan | University of Stuttgart |
Berberich, Julian | University of Stuttgart |
Allgower, Frank | University of Stuttgart |
Keywords: Data-based control, Predictive control, Linear systems
Abstract: In this paper, we propose a data-driven economic model predictive control (EMPC) scheme with generalized terminal constraint to control an unknown linear time-invariant system. Our scheme is based on the Fundamental Lemma to predict future system trajectories using a persistently exciting input-output trajectory. The control objective is to minimize an economic cost objective. By employing a generalized terminal constraint with artificial equilibrium, the scheme does not require prior knowledge of the optimal equilibrium. We prove that the asymptotic average performance of the closed-loop system can be made arbitrarily close to that of the optimal equilibrium. Moreover, we extend our results to the case of an unknown linear stage cost function, where the Fundamental lemma is used to predict the stage cost directly. The effectiveness of the proposed scheme is shown by a numerical example.
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11:00-11:20, Paper WeA19.4 | |
A Data Based System Representation |
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Szabo, Zoltan | SZTAKI |
Bokor, Jozsef | Hungarian Academy of Sciences |
Gaspar, Peter | SZTAKI |
Keywords: Linear systems, Time-invariant systems, Data-based control
Abstract: The paper proposes a system representation formed by a minimal collection of sufficiently long restricted trajectories generated by an observable discrete time LTI system. Conditions are given under which such a collection is a system representation and also an exhaustive parametrization of these representations is provided. These can be also interpreted as a generalized persistency condition which complements the results encountered for the controllable case. In terms of the proposed representation some system properties are investigated and a controllable--autonomous decomposition is given. Finally it is shown how the representation associated to the inverse system, to the parallel and cascade connection, respectively, can be derived.
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11:20-11:40, Paper WeA19.5 | |
Synthesis of Controllers for Partially-Observable Systems: A Data-Driven Approach |
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Jahanshahi, Niloofar | Ludwig Maximilian University of Munich |
Zamani, Majid | University of Colorado Boulder |
Keywords: Data-based control, Sampled-data control
Abstract: This paper is concerned with the formal synthesis of safety controllers for partially-observable continuous-time polynomial-type systems with unknown dynamics. Given a continuous-time polynomial-type estimator with a partially-unknown dynamic and a known upper bound on the estimation accuracy, we propose a data-driven approach to compute a polynomial-type controller ensuring safety of the system. The proposed framework is based on a notion of so-called control barrier functions and only requires a single output trajectory collected from the system and a single state trajectory collected from its estimator. We show the application of our technique by synthesizing a safety controller for a partially-observable jet engine with unknown dynamics.
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11:40-12:00, Paper WeA19.6 | |
Deep Kernel Learning-Based Bayesian Optimization with Adaptive Kernel Functions |
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Wang, Xizhe | Tsinghua University |
Hong, Xufeng | Peking University |
Pang, Quanquan | Peking University |
Jiang, Benben | Tsinghua University |
Keywords: Data-based control, Machine learning in modelling, prediction, control and automation, Data-driven optimal control
Abstract: Bayesian optimization (BO) is a widely used data-driven method for the global optimization of black-box objective functions with noise. A key component of BO is surrogate model that is a probabilistic model used for approximating black-box objective functions. However, classical BO methods often utilize Gaussian processes with stationary covariance functions as surrogate models, which is difficult to accurately model complex systems with rapidly oscillating target functions, and therefore deteriorates the performance of BO. To this end, a Bayesian optimization approach based on deep kernel learning (DKL) is investigated for the optimization of complex objective functions with large oscillations, in which a Gaussian process based on deep kernel learning is utilized to capture the characteristics of data with non-stationary and hierarchical covariance functions via deep neural networks. The optimization performance of the DKL-based BO approach with different network structures is quantified and compared with a state-of-the-art BO method based on Gaussian process under the scenarios of different noise levels.
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WeA20 |
Room 421 |
Fault-Tolerant Control |
Regular Session |
Chair: Xu, Feng | Tsinghua Univerisity |
Co-Chair: Padhi, Radhakant | Indian Institute of Science |
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10:00-10:20, Paper WeA20.1 | |
A New Method to Compute Minimal Detectable and Isolable Faults of Active Fault Diagnosis |
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Chen, Sanchuan | Tsinghua University |
Liu, Houde | Tsinghua University |
Xu, Feng | Tsinghua Univerisity |
Liang, Bin | Tsinghua University |
Keywords: Diagnosis, Linear systems, Time-invariant systems
Abstract: This paper proposes a new method for the computation of guaranteed minimal detectable and isolable faults of set-based active fault diagnosis for multiplicative actuator faults. Compared with our previous work, the proposed method in this paper has the important advantage of low computational complexity. In particular, by handling the coupling of faults and inputs and using an objective function describing the minimal detectable and isolable faults, a new two-step optimization method is proposed to analyze and compute the minimal detectable and isolable faults. At the end of this paper, two examples are used to show the effectiveness of the proposed method and the advantage of low computational complexity.
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10:20-10:40, Paper WeA20.2 | |
Dependability Management of Control Systems Via Controller Design |
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Suyama, Koichi | Tokyo Univ. of Marine Science and Technology |
Miura, Rinka | Tokyo University of Marine Science and Technology |
Sebe, Noboru | Kyushu Institute of Technology |
Keywords: Fault-tolerant, Linear systems, Robust control (linear case)
Abstract: We propose dependability management of control systems via controller design under the authorization by international standards. We can obtain a controller achieving a given target value of availability and the optimal performance in the normal operation. Furthermore, we show quantitatively the existence of the trade-off between the availability target and control performance first time ever. This is meaningful for the further developments in fault-tolerant control.
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10:40-11:00, Paper WeA20.3 | |
Longitudinal Control of an Over-Actuated Off-Road Vehicle with Fault Tolerance and Longitudinal Slip Consideration |
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Vera, Solenne | Université De Haute-Alsace |
Basset, Michel | Université De Haute-Alsace |
Keywords: Fault-tolerant, Adaptive and robust control of automotive systems, Lyapunov methods
Abstract: A new fault-tolerant longitudinal control allocation is developed in this paper in order to distribute the different torques considering that the vehicle involved is an electrical four wheel driving vehicle. Its purpose is to keep an acceleration set-point given by the driver and to reckon with the wheels slip that can occur in an off-road terrain. The method is based on a constrained dynamic pseudo-inverse allocation.
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11:00-11:20, Paper WeA20.4 | |
Nussbaum Gain-Based Cone Angle Constrained Fault-Tolerant Attitude Control with Time-Varying Inertia |
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Vutukuri, Srianish | Indian Institute of Science |
Padhi, Radhakant | Indian Institute of Science |
Keywords: Fault-tolerant, Adaptive control, Constrained control
Abstract: This paper proposes a robust adaptive attitude control law for handling a class of actuator faults in the presence of various challenges, such as time-varying inertia, attitude constraints, and input saturation. The proposed approach uses cone angles to represent orientation errors, which are constrained within a performance function to ensure desired transient and steady-state behaviour during reference tracking. Input saturation is approximated using a smooth hyperbolic tangent function. The Nussbaum gain technique is used to handle the unknown control coefficients, which guarantees uniformly ultimately bounded stability in the presence of uncertainties and disturbances. The paper also proposes a norm-based disturbance approximation to estimate the total uncertainty during the Lyapunov analysis. Numerical simulations demonstrate the effectiveness of the proposed control law.
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11:20-11:40, Paper WeA20.5 | |
Timing-Robust Control Over the Cloud Using On-Line Parametric Optimization |
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Nyberg Carlsson, Max | Lund University |
Vreman, Nils | Lund University |
Cervin, Anton | Lund Univ |
Keywords: Fault-tolerant, Data-driven robust control, Adaptive control
Abstract: In this paper, we present a heuristic method for adapting a networked linear feedback controller to improve its robustness to timing complications, such as long delays, aborted computations, and dropped packets. The core concept of the approach is to log successful sampling and actuation events and then, at discrete time-points, use non-convex parametric optimization to improve the expected performance of the controller under the assumption that the future timing behavior will be similar to the current one. To reduce the time complexity of the optimization algorithm, automatic differentiation is integrated for efficient gradient descent. The approach is evaluated on a physical ball and beam plant, where both the controller and optimization algorithm can be located in the Cloud.
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11:40-12:00, Paper WeA20.6 | |
Support Technology for Preventive Maintenance of Control Systems Based on Fail-Soft Concept |
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Suyama, Koichi | Tokyo Univ. of Marine Science and Technology |
Sebe, Noboru | Kyushu Institute of Technology |
Keywords: Fault-tolerant, Linear systems, Switching stability and control
Abstract: In this paper, as a support technology for safely performing preventive maintenance of LTI control systems, we propose a safe shutdown process for a maintenance-object subsystem. The proposed process is based on the ``fail-soft'' concept that the subsystem gradually makes its way toward a complete stoppage and the overall control system is lead to a safe situation by using the remaining function in the overall system including the subsystem. The discussion in this paper can be applied to a return process to the normal operation.
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WeA21 |
Room 422 |
Navigation and Control |
Regular Session |
Chair: Tanaka, Takashi | University of Texas at Austin |
Co-Chair: Tazaki, Yuichi | Kobe University |
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10:00-10:20, Paper WeA21.1 | |
Switching Formation Control of Multi-Lane Autonomous Vehicle Platoons Robust to Relative Position Measurement Noises |
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Meere, Bastiaan Guillermo Lorenzo | Eindhoven University of Technology |
Fidan, Baris | University of Waterloo |
Heemels, Maurice | Eindhoven University of Technology |
Keywords: Cooperative navigation, Multi-vehicle systems, Multi-agent systems
Abstract: This paper studies formation control of multi-lane platoons of vehicles, endowed with local positioning capabilities, under the influence of noises and inconsistencies of inter-vehicle relative position measurements. We propose a distributed two-level control framework that consists of a high-level relative position based distributed formation control scheme and low-level individual dynamic controllers of the platoon vehicles. The proposed formation control scheme utilizes deadzone based switching for robustness against sensor noises and adaptive longitudinal controllers for enabling the platoon of heterogeneous vehicles to track the desired platoon velocity.
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10:20-10:40, Paper WeA21.2 | |
Cooperative Adaptive Cruise Control for Heterogeneous Platoons with Actuator Delay |
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de Haan, Redmer | Eindhoven University of Technology |
van der Sande, Tom | Eindhoven University of Technology |
Lefeber, Erjen | Eindhoven Univ of Technology |
Keywords: Cooperative navigation, Multi-vehicle systems, Motion control
Abstract: Cooperative adaptive cruise control (CACC) is a control method that enables close vehicle following with string stable behavior, i.e., disturbances are not amplified through the vehicle string. Consequently, the technique contributes to increased road throughput and safety. General practice in CACC design is to describe the longitudinal vehicle dynamics by a simple first order model. For certain vehicles, however, this model has to be extended by an input delay to better represent the longitudinal behavior. In this paper, we show that the performance of a class of heterogeneous CACC controllers greatly deteriorates when the ego vehicle has a delay in the driveline. The minimum required string stable timegap increases to such a degree, that the controller is no longer suitable for close vehicle following. By implementing a Smith predictor in the control scheme, the delay is compensated, restoring the string stability properties. However, the original vehicle following objective is no longer fulfilled with the inclusion of the Smith predictor. By adopting an alternative timegap, the original control objective is restored for steady state situations, enabling CACC for heterogeneous platoons with actuator delays.
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10:40-11:00, Paper WeA21.3 | |
Facilitating Cooperative and Distributed Multi-Vehicle Lane Change Maneuvers |
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Kim, Hansung | University of California, Berkeley |
Borrelli, Francesco | University of California |
Keywords: Multi-vehicle systems, Cooperative navigation, Autonomous vehicles
Abstract: A distributed coordination method for solving multi-vehicle lane changes for connected autonomous vehicles (CAVs) is presented. Existing approaches to multi-vehicle lane changes are passive and opportunistic as they are implemented only when the environment allows it. The novel approach of this paper relies on the role of a facilitator assigned to a CAV. The facilitator interacts with and modifies the environment to enable lane changes of other CAVs. Distributed MPC path planners and a distributed coordination algorithm are used to control the facilitator and other CAVs in a proactive and cooperative way. We demonstrate the effectiveness of the proposed approach through numerical simulations. In particular, we show enhanced feasibility of a multi-CAV lane change in comparison to the simultaneous multi-CAV lane change approach in various traffic conditions generated by using a data-set from real-traffic scenarios.
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11:00-11:20, Paper WeA21.4 | |
Virtual Yaw Rate Display for Reducing Steering Instability of Remote Driving |
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Ohgashira, Junji | Kobe University |
Tazaki, Yuichi | Kobe University |
Nagano, Hikaru | Kobe University |
Yokokohji, Yasuyoshi | Kobe Univ |
Kameoka, Shota | Mitsubishi Electric |
Keywords: Teleoperation, Guidance, navigation and control of vehicles
Abstract: In vehicle teleoperation, reducing instability of driving caused by communication delay is one of important technical problems. This study proposes a passivity-based vehicle teleoperation system that compensates for the delay of visual information presented to the driver. The proposed method applies wave variable transformation to steering angle and yaw rate, and presents modified yaw rate to the driver by altering the viewing direction of camera images. This effectively makes the driver feel that the vehicle responds to his/her steering operation without delay, and consequently over-steering is greatly reduced. The results of experiments using a driving simulator showed that the proposed method greatly improves lateral stability of driving.
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11:20-11:40, Paper WeA21.5 | |
Two-Region Perimeter Control Based on Risk-Averse Model Predictive Control |
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Shi, Yun Tao | North China University of Technology |
Zhang, Ying | North China University of Technology |
Yin, Xiang | North China University of Technology |
Zhou, Meng | North China University of Technology |
Wang, Guishuai | North China University of Technology |
Bai, Chonghao | North China University of Technology |
Keywords: Intelligent Transportation Systems, Modelling and control of road traffic networks
Abstract: The perimeter control is effective in alleviating traffic congestion. However, previous studies about perimeter control based on macroscopic fundamental diagram didn’t consider the influences of the system uncertainty even though this uncertainty may lead to significant congestion. This paper presents a two-region perimeter control method based on a risk-averse model predictive control considering uncertainty. The advantage of this paper is that we design a risk index for uncertainty and design a controller which takes the risk index as an optimization objective. A scenario tree is used to model the uncertainty of the two-region dynamic equations. Average value at risk mapping is employed to calculate the systematic risk due to uncertainty. Then, the optimization objective of a multi-stage risk is used in MPC based on the scenario tree. Finally, the multi-stage risk is formulated as a solvable form. Simulation results show that the proposed perimeter control method reduces the total travel time of the two-region road network with uncertainty and significantly reduces traffic congestion compared to the stochastic model predictive control method.
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11:40-12:00, Paper WeA21.6 | |
Upper and Lower Bounds for End-To-End Risks in Stochastic Robot Navigation |
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Patil, Apurva | The University of Texas at Austin |
Tanaka, Takashi | University of Texas at Austin |
Keywords: Autonomous vehicles, Autonomous systems, Trajectory tracking and path following
Abstract: We present an analytical method to estimate the collision probability of motion plans for autonomous agents with discrete-time dynamics operating under Gaussian motion and sensing uncertainty. Motion plans generated by planning algorithms cannot be perfectly executed by autonomous agents in reality due to the inherent uncertainties in the real world. Estimating end-to-end collision probability is crucial to characterize the safety of trajectories and plan risk-optimal trajectories. In this work, we derive upper and lower bounds for end-to-end collision probability of motion plans using results from probability theory including the inequalities of Hunter, Kounias, Frechet, and Dawson. Using a ground robot navigation example, we demonstrate that our method is considerably faster than the naive Monte Carlo sampling method and the proposed bounds are significantly less conservative than Boole’s bound commonly used in the literature.
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WeA22 |
Room 423 |
Control, Mechatronics, and Imaging for Medical Devices and Systems in
Medicine I |
Open Invited Session |
Chair: Desaive, Thomas | University of Liege |
Co-Chair: Chase, J. Geoffrey | University of Canterbury |
Organizer: Desaive, Thomas | University of Liege |
Organizer: Chase, J. Geoffrey | University of Canterbury |
Organizer: Schauer, Thomas | Technische Universitaet Berlin |
Organizer: Tsuzuki, Marcos de Sales Guerra | University of Sao Paulo |
Organizer: Benyo, Balazs | Budapest University of Technology and Economics |
Organizer: Moeller, Knut | Furtwangen University |
Organizer: Pretty, Christopher | University of Canterbury |
Organizer: Chiew, Yeong Shiong | Monash University |
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10:00-10:20, Paper WeA22.1 | |
Electrical Impedance Tomography Hardware with Demodulation (I) |
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Benetti, Rafael | EPUSP |
Cavalheiro, André | EPUSP |
Nasiri, Hossein | EPUSP |
Takimoto, Rogerio Yugo | Escola Politecnica Da Universidade De Sao Paulo |
Duran, Guilherme C. | EPUSP |
Ueda, Edson Kenji | Escola Politecnica Da Universidade De Sao Paulo |
Okamura Ferro, Rafael Akira | Escola Politécnica Da USP |
Barari, Ahmad | University of Ontario Institute of Technology |
Martins, Thiago de Castro | University of Sao Paulo |
Tsuzuki, Marcos de Sales Guerra | University of Sao Paulo |
Keywords: Bio-signals analysis and interpretation, Biomedical and medical image processing and systems
Abstract: Electrical impedance tomography (EIT) is a promising imaging technology. It is portable, user-independent, and low cost (compared to other imaging technologies). There are two main approaches for EIT equipments: dynamic and absolute images. Absolute images are technologically more difficult and are limited by hardware. Phase information is required to create permittivity images. This is an ongoing research with the objective of evaluating the phase information. A new architecture with up to 64 electrodes is proposed. Each electrode has its own Howland current source and microcontroller. The proposed hardware consists of three main modules: the electrode hardware (with Howland current source and microcontroller); the demodulator algorithm; and, the electrode synchronizer. Some results are presented with the electrode hardware that demonstrate data acquisition with two electrodes. Tests with the demodulator algorithm were also presented. Simulated tests with the designed electrode synchronizer were performed, and the implementation remains, and it is considered a future work.
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10:20-10:40, Paper WeA22.2 | |
Influence of Reconstruction Algorithms on Harmonic Analysis in Electrical Impedance Tomography (I) |
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Stein, Erik | Institute of Technical Medicine (ITeM), Hochschule Furtwangen |
Chen, Rongqing | Furtwangen University |
Battistel, Alberto | Furtwangen University |
Lovas, András | Kiskunhalas Semmelweis Hospital |
Benyo, Balazs | Budapest University of Technology and Economics |
Moeller, Knut | Furtwangen University |
Keywords: Medical imaging and processing, Developments in measurement, signal processing, Decision support and control
Abstract: Electrical Impedance Tomography (EIT) is a commonly used imaging technique for monitoring respiration on the bedside and it might have the potential for monitoring lung perfusion. Several signal processing approaches have been developed to separate respiration and perfusion. In this contribution we investigated whether different image reconstruction algorithms influence the separation results provided by the harmonic analysis approach. We compared the algorithms used by Dräger, the Gauss-Newton method with different regularizers as well as the GREIT algorithm. The comparison was carried out using a retrospective EIT dataset from a COVID-19 patient. The results gave insight that the harmonic analysis separation approach is dependent on the reconstruction algorithms. Both, the separation of the perfusion and the separation of the respiration showed differences between the reconstruction algorithms when carried out pixel-wise. On the other hand, the separations carried out on the global impedance only showed marginal differences for the separated perfusion.
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10:40-11:00, Paper WeA22.3 | |
Critical Assessment of Mammography Accuracy (I) |
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Fitzjohn, Jessica Louise | University of Canterbury |
Zhou, Cong | University of Canterbury |
Chase, J. Geoffrey | University of Canterbury |
Keywords: Medical imaging and processing
Abstract: Mammography is currently considered the gold standard for breast screening, despite painful breast compression, invasive radiation exposure and excessive infrastructure and personnel requirements, contributing to its inequity. Furthermore, sensitivity and specificity of mammography are often overstated by studies utilising flawed methodology. This paper critically reviews the literature reporting on methods used to calculate diagnostic accuracy of mammography. Values for sensitivity, specificity and receiver operator characteristic (ROC) curve area (AUC) are presented by averaging results from studies inclusive of a comparison to another breast screening modality. The result is mammography sensitivity of 60%, specificity of 80%, AUC of 0.73. These values should be used when assessing diagnostic performance of other breast screening technologies.
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11:00-11:20, Paper WeA22.4 | |
Surgical Tool Classification & Localisation Using Attention and Multi-Feature Fusion Deep Learning Approach (I) |
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Jalal, Nour Aldeen | Institute of Technical Medicine (ITeM), Furtwangen University |
Abdulbaki Alshirbaji, Tamer | Institute of Technical Medicine (ITeM), Furtwangen University |
Docherty, Paul D | University of Canterbury |
Arabian, Herag | Hochschule Furtwangen University, Institute of Technical Medicin |
Neumuth, Thomas | Universität Leipzig |
Moeller, Knut | Furtwangen University |
Keywords: Biomedical and medical image processing and systems, Decision support and control, Medical imaging and processing
Abstract: Analysing laparoscopic videos, particularly for surgical tool classification and localisation, has attained interest in the field of surgical data science since they represent an extensive information source. However, the difficulties for acquiring and labelling these videos have led to paucity of labelled datasets. Consequently, the progress of developing robust and generalised surgical tool detection models was slowed down, and translating these models into the medical field was hindered. In this work, supervised surgical tool classification and weakly-supervised tool localisation in laparoscopic videos were addressed. A base convolutional neural network (CNN) model was adapted to perform both tasks by incorporating multi-map localisation layers. Squeeze-and-excitation modules were added to the CNN to enhance the ability of the model to generate better focused informative features. Additionally, features at multiple stages of the CNN were combined and fused in a batch normalisation layer to enhance model generalisability. The proposed model was evaluated on the popular Cholec80 dataset. Experimental results of 94.1% mean average precision for tool classification and 70.1% F1-score for tool localisation revealed the ability of the model to learn better features for both tasks. The proposed approach showed the advantages of integrating attentions modules and multi-stage features fusion technique for surgical tool classification and localisation.
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11:20-11:40, Paper WeA22.5 | |
Influence of the Patient-Specific Structural Prior Mask on Image Reconstruction Using the Discrete Cosine Transform-Based EIT Algorithm (I) |
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Chen, Rongqing | Furtwangen University |
Battistel, Alberto | Furtwangen University |
Krueger-Ziolek, Sabine | Furtwangen University |
Stein, Erik | Institute of Technical Medicine (ITeM), Hochschule Furtwangen |
Fairbairn, Katharine | James Watt School of Engineering, University of Glasgow |
Chase, J. Geoffrey | University of Canterbury |
Rupitsch, Stefan | University of Freiburg |
Moeller, Knut | Furtwangen University |
Keywords: Biomedical and medical image processing and systems, Biomedical system modeling, simulation and visualization, Medical imaging and processing
Abstract: Electrical impedance tomography (EIT) is an imaging technology but suffers greatly from the ill-posed inverse problem when reconstructing an image, which is mainly caused by the high degrees of freedom and the relatively large measurement noise. The use of discrete cosine transform (DCT) to cluster finite elements has been proposed to reduce the degrees of freedom in inverse computations. However, blurred anatomical alignment and artifacts still present challenges to the interpretation of EIT images. Incorporating prior information into the reconstruction process has been reported to enhance the quality of EIT images. In this contribution, we propose the use of a patient-specific structural prior mask for the DCT-based EIT algorithm. We evaluate the influence of this mask on simulation models with varying ventilation statuses. Our results demonstrate that the structural prior mask preserves the morphological structures of the lungs and avoids blurring of the solution, thereby facilitating EIT image interpretation for clinicians.
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11:40-12:00, Paper WeA22.6 | |
Two U-Net Architectures for Infant Brain Tissue Segmentation from Multi-Spectral MRI Data (I) |
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Dénes-Fazakas, Lehel | Óbuda University |
Kovacs, Levente | Obuda University |
Eigner, György | Óbuda University |
Szilagyi, Laszlo | Obuda University |
Keywords: Medical imaging and processing, Biomedical and medical image processing and systems, Decision support and control
Abstract: The segmentation of brain tissues based on MRI data represents a widely investigated problem in medical image analysis. Infant brain tissues in the so-called isointense phase of development, around the age of 6 to 9 months, are difficult to segment due to the inherent myelination and maturation processes, which manifest in grey and white matter pixel intensity distributions severely overlapping in both T1-weighted and T2-weighted MRI data. This paper introduces two different U-net architectures, one with 2D convolution and this other with 3D convolution, and employs them in infant brain tissue segmentation based on multi-spectral MRI data. The proposed methods are trained and tested on the training data set of the iSeg-2017 challenge. All records were initially fed to histogram alignment that was independently performed on each data channel. Nine records were used for training and one record for testing in each evaluation round, but all ten records took their turn as testing data. Statistical accuracy indicators were employed to assess the segmentation accuracy of both network models. The U-net architecture preforming 3D convolution obtained the better segmentation, achieving 91.8% average rate of correct decisions, and 95.0%, 91.5% and 89.8% Dice similarity score for cerebro-spinal fluid, grey matter, and white matter tissues, respectively.
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WeA23 |
Room 501+502 |
Advances Toward Smart Digitized Shopfloors I |
Open Invited Session |
Chair: Cohen, Yuval | Afeka Tel Aviv College of Engineering |
Co-Chair: Macchi, Marco | Politecnico Di Milano |
Organizer: Cohen, Yuval | Afeka Tel Aviv College of Engineering |
Organizer: Macchi, Marco | Politecnico Di Milano |
Organizer: Negri, Elisa | Politecnico Di Milano |
Organizer: Faccio, Maurizio | University of Padova |
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10:00-10:20, Paper WeA23.1 | |
A Framework for Integrating Artificial Intelligence in Digital Twins of Manufacturing Systems (I) |
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Cohen, Yuval | Afeka Tel Aviv College of Engineering |
Aperstein, Yehudit | Afeka |
Reis, João | Academia Militar |
Keywords: Digital twins for manufacturing, Intelligent manufacturing systems, Smart manufacturing
Abstract: Both Digital Twins (DTs) and Artificial Intelligence (AI) are major elements in the Industry 4.0 paradigm. However, while DTs embody the Cyber Physical Systems (CPS) vision of connected and digitally controlled world, AI integration in DT has no clear and agreed upon framework. In this paper we focus on DTs in Industry 4.0 environments and characterize the implementation of AI in these DTs. In the first part of the paper, we review the relevant literature. In the second part of this paper, we discuss the challenges for integrating AI in DT. Finally, we identify both practical and research potential of this integration and discuss their advantages and shortcomings, as well as difficulties that are expected in their deployment.
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10:20-10:40, Paper WeA23.2 | |
Multi-Objective Multi-Resource Task Allocation for Collaborative Robots Systems (I) |
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Granata, Irene | Università Degli Studi Di Padova |
Faccio, Maurizio | University of Padova |
Cohen, Yuval | Afeka Tel Aviv College of Engineering |
Keywords: Human-centric manufacturing, Intelligent manufacturing systems, Human-automation integration
Abstract: The shift from Industry 4.0 to Industry 5.0 has led to a greater focus on workers' needs in the workplace. Collaborative robots have been introduced to promote a fair division of tasks and reduce physical and mental strain on workers. However, there is a lack of research on how to implement human-centered task allocation. This study proposes a model for multi-objective task allocation, including minimizing makespan, energy expenditure, and mental workload. The study also suggests a method for evaluating mental workload. Results show that the strictness of task sequence affects makespan and energy expenditure, and a new constraint related to idle times is proposed. The optimal level of worker saturation is one that minimizes makespan while minimizing increases in energy expenditure and mental workload.
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10:40-11:00, Paper WeA23.3 | |
Real-Time Field Synchronization Mechanism for Digital Twin of Manufacturing Systems (I) |
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Abdoune, Farah | Nantes University |
Cardin, Olivier | LS2N UMR CNRS 6004 - Nantes University - IUT De Nantes |
Nouiri, Maroua | LS2N - Nantes Université, France |
Castagna, Pierre | Univ of Nantes |
Keywords: Digital twins for manufacturing, Discrete event systems in manufacturing
Abstract: Digital Twin (DT) is one of the promising digital technologies being developed at present to support digital transformation. Successful DT execution needs real-time access to collected data. However, real-time connection and synchronization are a significant difficulty, owing to the physical environment's unique characteristics such as variability, uncertainty, the different scales of the physical and virtual spaces, and the data generated continuously by various entities. Prior research has been conducted to address the DT synchronization problem in the literature. However, there is a lack of standard ap-proaches or mechanisms for digital twins at the field level in manufacturing systems. Hence, this paper aims to present a reliable field synchronization mechanism for DT of manufacturing systems for real-time data.
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11:00-11:20, Paper WeA23.4 | |
Automatic Routing Reconfiguration for Fault Tolerance in Smart Manufacturing Plants (I) |
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De Santis, Sonia | KU Leuven |
Boffadossi, Roberto | National Research Council (CNR) |
Fagiano, Lorenzo | Politecnico Di Milano |
Keywords: Flexible and reconfigurable manufacturing systems, Smart manufacturing, Manufacturing plant control
Abstract: This paper focuses on the parts routing problem in a reconfigurable manufacturing plant, in presence of potential faults and uncertainty on the job scheduling and duration. The plant is modeled as a directed graph, where the nodes represent either transportation modules or machines, and the edges represent the allowed transitions between adjacent nodes. The parts move across the plant along predefined sequences of nodes, therefore the system state tracks the progress of the parts along such sequences and the control inputs are the transitions to be activated to command the parts movement. Provided the sequences, the proposed method automatically generates feedback control rules for deadlock avoidance, which are employed by a path following strategy to compute the suitable control inputs, complying with given temporal-logic constraints and avoiding deadlock states. Additionally, the approach is extended to deal with faults affecting the transportation modules via the selection of new feasible sequences and the online reconfiguration of the system state. Finally, the proposed approach is tested in high-fidelity simulations, showing high computational efficiency and throughput.
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11:20-11:40, Paper WeA23.5 | |
A Conceptual Framework for Digital Twins in Production Scheduling and Control (I) |
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Macchi, Marco | Politecnico Di Milano |
Ragazzini, Lorenzo | Politecnico Di Milano |
Negri, Elisa | Politecnico Di Milano |
Keywords: Digital twins for manufacturing, Advanced planning and scheduling, Manufacturing plant control
Abstract: The interest in enhancing decision-making using Digital Twins in production systems is increasing in the recent years. However, most of the scientific contributions in the field lack of generality as they focus specific problem instances, overburdening the search for a common thread. To help overcoming this issue, the authors propose a conceptual framework in order to analyze the role of Digital Twins in applications in different production environments, with specific concern on production scheduling and control. The analysis is achieved by responding to three main questions, which focus on the application, the integration, and the functionality of the Digital Twin. The framework is applied to describe six relevant use cases of Digital Twins within this research area.
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11:40-12:00, Paper WeA23.6 | |
Non-Intrusive Musculoskeletal Disorders Risk Assessment towards an Integration in Human Operators’ Digital Twins (I) |
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Murcia, Nicolas | LS2N - Nantes University |
Mohafid, Abdelmoula | Université De Nantes |
Cardin, Olivier | LS2N UMR CNRS 6004 - Nantes University - IUT De Nantes |
Keywords: Digital twins for manufacturing, Human-centric manufacturing, Cyber-physical production systems
Abstract: The digital twin of human operators is an important aspect of future cyber-physical production systems. Among the various usage of this twin, the possibility to assess the health of the operator, especially fatigue and musculoskeletal disorders, is a major stake for future organizations. If this problem is often dealt with in the case of repetitive operations, mostly through an ergonomic perspective, it is much more difficult to evaluate the impact of non-repetitive operations on the health of the operators. This study aims at providing a first step to this objective, by exhibiting the correlation between ergonomic evaluations of operations difficulty with the MUSKA MSD methodology and the pain felt by the operators through a longitudinal study performed through NORDIC questionnaires. The results show that the results of ergonomic evaluation of operations can be used in a stochastic parametric model to assess the evolution of pains of the operators on long time scales.
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WeB01 |
Main Hall |
Connected and Autonomous Vehicle Applications: Estimation Perspectives |
Open Invited Session |
Chair: Zemouche, Ali | CRAN UMR CNRS 7039, University of Lorraine |
Co-Chair: Belkhatir, Zehor | University of Southampton |
Organizer: Zemouche, Ali | CRAN UMR CNRS 7039, University of Lorraine |
Organizer: Belkhatir, Zehor | University of Southampton |
Organizer: Rajamani, Rajesh | Univ. of Minnesota |
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13:30-13:50, Paper WeB01.1 | |
High-Gain Like Observer Design for Nonlinear Systems Applied to Vehicle Motion Estimation (I) |
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Bessafa, Hichem | Université De Lorraine (CRAN) |
Delattre, Cédric | Université De Lorraine (IUT De Longwy) |
Belkhatir, Zehor | University of Southampton |
Zemouche, Ali | CRAN UMR CNRS 7039, University of Lorraine |
Rajamani, Rajesh | Univ. of Minnesota |
Keywords: Vehicle dynamic systems, Autonomous vehicles
Abstract: This work investigates the problem of state estimation for nonlinear triangular systems having additional output measurements. The main objective of this paper is to propose observer design strategies that account for the available additional information, which is difficult to consider using the standard high-gain observer methodology. To deal with this challenge, we propose a novel observer design method to handle the additional output measurements. This method can be thought of as an extension of the standard high-gain observer by introducing a weighting matrix as a tuning parameter, which uses both the high-gain methodology and the LPV/LMI technique. The proposed approach was applied to a nonlinear longitudinal dynamic model that uses extra measurement information, in addition to the measured longitudinal position of the vehicle.
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13:50-14:10, Paper WeB01.2 | |
LPV Unknown Input Observer-Based Estimation of Driver Intervention Torque and Vehicle Dynamics for Human-Machine Shared Driving (I) |
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Nguyen, Anh-Tu | INSA Hauts-De-France, Université Polytechnique Hauts-De-France |
Guerra, Thierry Marie | Polytechnic University Hauts-De-France Valenciennes |
Lu, Jiyun | North Minzu University |
Pan, Juntao | North Minzu University |
Taghavifar, Hamid | Concordia University |
Keywords: Vehicle dynamic systems, Human and vehicle interaction, Design, control and monitoring of autonomous transportation systems
Abstract: This paper presents an unknown input observer (UIO)-based method to jointly estimate the vehicle dynamics and the driver torque within the framework of human-machine shared driving. To deal with the time-varying vehicle longitudinal speed, the vehicle dynamics is represented as a linear parameter-varying (LPV) model. Based on an unknown input (UI) decoupling technique, an LPV observer is designed, which can guarantee an asymptotic estimation performance of both the vehicle dynamics and the driver torque. Via Lyapunov stability theory, we propose sufficient conditions, expressed in terms of linear matrix inequalities, to design LPV UIO. High-fidelity Simulink-CarSim co-simulations are carried out to show the effectiveness of the proposed LPV UIO-based estimation method for driver-automation shared driving dynamics. Moreover, a comparative study is performed with a recent LPV estimation method to highlight the practical interests of the new solution.
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14:10-14:30, Paper WeB01.3 | |
Continuous–Discrete Time Neural Network Observer for Nonlinear Dynamic Systems Application to Vehicle Systems (I) |
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Abdl Ghani, Hasan | University of Rouen Normandy |
Ahmed Ali, Sofiane | Universite Paris-Saclay |
Laghmara, Hind | Université Haute-Alsace (UHA), Modélisation Intelligence Process |
Ainouz, Samia | INSA Rouen Normandie |
Gao, Xing | IRSEEM LAB |
Khemmar, Redouane | Normandy University, UniROUEN, ESIGELEC, IRSEEM |
Keywords: Neural networks, Vehicle dynamic systems
Abstract: This paper proposes a novel continuous-discrete (sampled data) time neural network (NSNN) observer for nonlinear systems. It can therefore be applied to systems with a high degree of non-linearity with no prior knowledge of the system dynamics. The proposed observer is a three-layer feedforward neural network that has been intensively trained using the error backpropagation learning algorithm, which includes an e-modification term to ensure robustness of the observer. A structure of the output predictor with a corrective term is added in the structure of the NN observer to overcome the problem of discrete time measurement. Simulations using MATLAB and CarSim are illustrated to demonstrate the performance of the proposed state observer strategy to reconstruct the state variables and parameters of a vehicle system.
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14:30-14:50, Paper WeB01.4 | |
Identifying Nudging Behaviour in Real-World Traffic Data Sets (I) |
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Li, Jing | Southeast University |
Liu, Di | Technical University of Munich |
Baldi, Simone | Southeast University |
Keywords: Modelling and control of road traffic networks, Human and vehicle interaction, Human factors in traffic and transportation control
Abstract: The vehicle nudging principle describes how a vehicle in the traffic flow induces a ‘pushing effect’ to its preceding vehicle. When combined with the traditional vehicle-following behaviour, the nudging principle enables bidirectional inter-vehicle interactions (look-ahead-and-behind). Unfortunately, despite numerical examples and traffic simulators indicating that nudging may improve the traffic flow, such results use artificially engineered scenarios. By using the NGSIM real-world traffic data sets, this work suggests that the nudging effect is a part of human-driven traffic as well, and can be suitably identified.
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14:50-15:10, Paper WeB01.5 | |
Safe Intersection Coordination with Mixed Traffic: From Estimation to Control |
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Chen, Xiao | KTH Royal Institute of Technology |
Jiang, Frank J. | KTH Royal Institute of Technology |
Narri, Vandana | KTH Royal Institute of Technology |
Adnan, Mustafa | Scania |
Mårtensson, Jonas | KTH Royal Institute of Technology |
Johansson, Karl H. | KTH Royal Institute of Technology |
Keywords: Intelligent Transportation Systems, Sensor integration and perception, Multi-vehicle systems
Abstract: In this paper, we propose an integrated framework for safe intersection coordination of connected and automated vehicles (CAVs) in mixed traffic. An intelligent intersection is introduced as a central node to orchestrate state data sharing among connected agents and enable CAV to acknowledge the presence of human-driven vehicles (HDVs) beyond the line of sight of onboard sensors. Since state data shared between agents might be uncertain or delayed, we design the intelligent intersection to safely compensate for these uncertainties and delays using robust set estimation and forward reachability analysis. When the intersection receives state data from an agent, it first generates a zonotope to capture the possible measurement noise in the state estimate. Then, to compensate for communication and processing delays, it uses forward reachability analysis to enlarge the set to capture all the possible states the agent could have occupied throughout the delays. Finally, using the resulting set as the initial condition, a distributed model predictive control onboard the CAV will plan an invariant safe motion by considering the worst-case behavior of human drivers. As a result, the vehicle is guaranteed to be safe while driving through the intersection. A prototype of our proposed framework is implemented using the Small-Vehicles-for-Autonomy (SVEA) platform. The effectiveness of our framework is evaluated in experiments based on a challenging scenario where the collision would have occurred without efficient coordination.
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15:10-15:30, Paper WeB01.6 | |
Real-Time Single-Frequency Precise Point Positioning for Connected Autonomous Vehicles: A Case Study Over Brazilian Territory |
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Oliveira E Silva, Felipe | Federal University of Lavras |
Hu, Wang | Univ. of California at Riverside |
Farrell, Jay A. | Univ. of California at Riverside |
Keywords: Navigation, guidance and control, Positioning systems, Autonomous vehicles
Abstract: Intelligent Transportation Systems (ITS) and Connected Autonomous Vehicles (CAV) are extremely active areas of research, which have attracted the attention of users, companies, and development agencies worldwide. The Global Navigation Satellite System (GNSS) is a main enabling technology, as ITS/CAV applications are fundamentally dependent on precise positioning systems. Among the recent GNSS technology advances that have allowed high accuracy to be achieved is Real-Time Precise Point Positioning (RT-PPP). Even though the Real-Time Service (RTS) of the International GNSS Service (IGS) provides various correction streams for RT-PPP deployment, some of them (e.g., those associated with ionospheric delays) still have limited accuracy. This has motivated local organizations and research institutes to deploy their own RT-PPP products, based on a denser regional network of GNSS Continuously Operating Reference Stations (CORS). The purpose of this work is to evaluate the performance of a recently established regional ionosphere RT-PPP product, from the Argentine University of La Plata (UNLP), which serves all of South America, with extensions to the Caribbean and Antarctica Peninsula. The main contributions of the work are: we show that RT-PPP using UNLP products outperforms RT-PPP using products exclusively from IGS-RTS; we benchmark positioning strategies, such as Post-Processed PPP (PP-PPP) and Relative Global Positioning System (RGPS); and, demonstrate the ability of Brazilian RT-PPP users employing Single-Frequency (SF) GPS code measurements and UNLP ionosphere products to achieve the CAV lane-level specification (i.e., 1-meter horizontal positioning accuracy at 95% probability). The article includes results from both static and moving experimental tests.
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WeB02 |
Room 301 |
Hybrid and Stochastic Systems |
Regular Session |
Chair: Lichtenberg, Gerwald | Hamburg University of Applied Sciences |
Co-Chair: Date, Hisashi | University of Tsukuba |
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13:30-13:50, Paper WeB02.1 | |
Linear State Signal Shaping Explicit Model Predictive Control Using Tensor Decompositions (I) |
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Pangalos, Georg | Fraunhofer Institute for Wind Energy Systems IWES |
Cateriano Yáñez, Carlos | Fraunhofer Institute for Wind Energy Systems IWES |
Meyer, Jan-Henrik | Hamburg University of Applied Sciences |
Lichtenberg, Gerwald | Hamburg University of Applied Sciences |
Keywords: Model predictive control of hybrid systems
Abstract: Due to the increasing use of nonlinear loads in modern power systems, harmonic currents have become a more prominent problem for power quality. Recently, a novel constrained linear state signal shaping model predictive controller has been proposed for shunt active power filter control. However, due to the high computational requirements of online quadratic programming solvers, this solution is not ready for real-time implementation. Therefore, the present work proposes the use of a linear state signal shaping explicit model predictive control formulation, such that the optimizations are done offline. To deal with the large memory footprint of the offline data generated, a tensor representation is introduced, which can then be compressed via tensor decomposition methods. The proposed approach was tested in simulation and was able to provide good results with a considerable reduction of the memory requirement.
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13:50-14:10, Paper WeB02.2 | |
Robust PMU Placement in Branch Switching Power Networks for Minimum Variance State Estimation (I) |
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Mishra, Aditya | University of California San Diego |
de Callafon, Raymond | University of California, San Diego |
Keywords: Estimation and filtering, Identifiability, Sensor networks
Abstract: Phasor Measurement Units (PMUs) are measurement devices that are installed on the buses of power network to measure voltage phasor data of a bus and current phasors of adjacent branches. With information on the power network impedance, a finite number of PMUs can be used to estimate the voltage on all buses, also known as the state of the power network. Traditionally, the problem of Optimal PMU Placement (OPP) focuses on having complete observability of the network state by strategically placing a minimum number of PMUs. A change in network topology caused, for example, by network switches, induces a change in the solution to the OPP problem. Since it is not feasible to change the locations of PMUs after every change in topology, the contribution of this paper is a PMU placement optimization algorithm which minimizes the variance on the estimated voltages and is also robust to the changes to the network topology. The robustness to the change in network topology is guaranteed by this optimization since it considers each change in the switch position as a different network topology and the optimization criterion is formulated as a multi-objective optimization function across all the different network topology caused by changing the switch positions. The proposed robust optimal placement algorithm can be implemented for both single current-channel PMU case and multi-current channel PMU case. The algorithm is tested on IEEE 14 bus network. The results show that the robust optimal placement can significantly reduce the effects of PMU measurement noise on the estimated states on average for different switch positions.
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14:10-14:30, Paper WeB02.3 | |
Kalman Filter Based Optimal Estimation of Injection Rate in Diesel Engine Application |
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Liu, Bingxin | Harbin Engineering University |
Fei, Hongzi | Harbin Engineering University |
Wang, Liuping | RMIT University |
Keywords: Kalman Filtering, Estimation and filtering, Nonparametric methods
Abstract: Real-time monitoring of fuel injection is significant for improving the accuracy of the injection control in diesel engines. To obtain the real-time injection information, this paper proposes an optimal estimation method for the fuel injection rate of high-pressure common rail system using the Kalman filter algorithm. A dynamic mathematical model between the rail pressure variation and injection rate is established based on the mechanism of fuel flow process. Then the Kalman filter for injection optimal estimation is designed. Finally, the estimation performance is verified by simulation. The results show that the estimated injection rate converges fast, and the deviations of injection volume between the estimated results and the actual values are less than 5%. The designed Kalman filter has successfully produced the optimal estimation of the fuel injection process.
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14:30-14:50, Paper WeB02.4 | |
Analysis and Control of Semi-Markov Jump Linear Systems Via Improved Utilization of Known Sojourn Information |
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Ning, Zepeng | Nanyang Technological University |
Zheng, Wei Xing | Western Sydney University |
Yin, Xunyuan | Nanyang Technological University |
Keywords: Synthesis of stochastic systems, Stability and stabilization of hybrid systems, Stochastic hybrid systems
Abstract: The paper investigates the mean-square stability and stabilization issues for discrete- time semi-Markov jump linear systems with fragmentary probabilistic distributions of sojourn time. As the probability distributions of the sojourn time are difficult to be completely reconstructed, the obtained probability mass functions of the sojourn time from the current mode to the target mode can be fragmentary. In view of this phenomenon, we propose a method that makes full utilization of all the known probabilistic information of the sojourn time to establish less conservative criteria for the stability and stabilization of semi-Markov jump linear systems than the methods that only leverage completely known probability mass functions of the sojourn time.
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14:50-15:10, Paper WeB02.5 | |
Hybrid State Estimation in a Semitrailer for Different Loading Conditions |
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Ehlers, Simon F. G. | Leibniz University Hannover |
Kortmann, Karl-Philipp | Leibniz University Hannover |
Kobler, Jan-Philipp | BPW Bergische Achsen KG |
Keywords: Estimation and filtering, Machine learning, Kalman filtering techniques in automotive control
Abstract: For state and parameter estimation in vehicles, Kalman filters, especially nonlinear extensions like the extended Kalman filter (EKF) and unscented Kalman filter (UKF), are very common. However, the estimation accuracy is highly dependent on the quality of the model used in the process update of the Kalman filter. Model errors can result from non-modeled dynamics that are either unknown or very difficult to describe. In recent years data-driven approaches for state estimation are the subject of research with promising results in estimation accuracy and reduced implementation effort. In this work, both a model-based method with an UKF and a data-driven approach based on recurrent neural networks (RNN) are implemented and combined to two hybrid methods for the application of state and parameter estimation in a truck-semitrailer for three different loading conditions. Hybrid estimation architectures promise to combine the advantages of model-based and data-driven methods to achieve better estimation accuracy than their standalone components. To the best knowledge of the authors, this work is the first to extend the field of hybrid state estimation to semitrailers estimating the truck steering angle, articulation angle, and the trailer's lateral and vertical tire forces. Four estimation architectures (an UKF, one purely data-driven method, and two hybrid methods) are optimized and compared to each other regarding estimation accuracy. The UKF is optimized with a particle swarm optimization (PSO) while the hyperparameters of the data-driven method are tuned with the asynchronous successive halving algorithm (ASHA) to result in a fair comparison. All methods are developed and compared based on an experimental data set from a test vehicle.
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15:10-15:30, Paper WeB02.6 | |
Monte Carlo Model Predictive Control for Underwater Snake Robot Locomotion |
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Qiu, Yiping | University of Tsukuba |
Date, Hisashi | University of Tsukuba |
Keywords: Predictive control, Randomized algorithms
Abstract: This paper studies a sample-based model predictive control using Monte Carlo sampling method. Different from gradient-based MPC, MCMPC is able to introduce discontinuous phenomena such as collisions into the system which makes it suitable for robot explorations in narrow space. In this study, MCMPC is utilized for the control of an underwater snake robot. Control of each joint angle as inputs may however highly increase the dimension of samplings and prediction steps, therefore we combine curvature derivative control (CDC) with MCMPC so that only one control input is needed to be generated for controlling whole snake robot locomotion without considering the quantity of links. The proposed MCMPC algorithm generates variable gait pattern while minimizing the difference between the position of center of mass of snake robot and the target point in the designed cost function. Experiments for snake robot consists of 5,10 and 20 links are tested, depends on the trajectory results we show that by introducing CDC into MCMPC, smoother locomotion could be achieved. Underwater snake robot can reach the set point and change its locomotion during operations with single control input by utilizing the proposed control method.
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WeB03 |
Room 302 |
Marine Robotics: The Breeze of Innovation and Remote Access to the Sea I |
Open Invited Session |
Chair: Bibuli, Marco | CNR-INM |
Co-Chair: Zereik, Enrica | Cnr - Inm |
Organizer: Bibuli, Marco | CNR-INM |
Organizer: Zereik, Enrica | Cnr - Inm |
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13:30-13:50, Paper WeB03.1 | |
The Blue-RoSES Project: A Gate for Remote Exploration of the Seas (I) |
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Bibuli, Marco | CNR-INM |
Caccia, Massimo | CNR-INM |
Claudia, Presicci | CNR |
Sebastiao, Luis | Instituto Superior Tecnico |
Cabecinhas, David | Instituto Superior Tecnico |
Potes, André | Instituto Superior Técnico |
Quintas, João | Instituto Superior Técnico |
Jacinto, Marcelo | Instituto Superior Técnico |
Pascoal, Antonio M. | Ist-Id, Vat 509830072 |
Keywords: Autonomous underwater vehicles, Control architectures in marine systems, Teleoperation
Abstract: This paper focuses on the description of the Blue-RoSES project, an European funded activity devoted to the development and exploitation of a reliable infrastructure for the remote employment of Remotely Operated Vehicles (ROVs) for both professional and recreational tasks. The paper firstly provides an overall view of the concept and then summarize the main modules composing the architecture and responsible for a reliable and stable remote piloting framework for ROVs. Analysis of the critical issues related to the remote piloting and control is carried out and measurements of the communication lags and delays are performed to obtain a statistical characterization, also providing a quantitative measure of the communication service. The reliability and performance of the complete system are demonstrated through experimental campaigns in real case scenarios.
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13:50-14:10, Paper WeB03.2 | |
A Geometric Path-Planning Algorithm for High Speed Marine Craft (I) |
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Ahmadi Dastgerdi, Karim | Queen’s University Belfast |
Singh, Bhawana | Queen's University Belfast United Kingdom |
Athanasopoulos, Nikolaos | Queen's University Belfast |
Naeem, Wasif | Queen's University of Belfast |
Lecallard, Benoit | Artemis Technologies Ltd |
Keywords: Marine system navigation, guidance and control, Autonomous surface vehicles, Dynamic positioning
Abstract: We propose a new geometric algorithm for path planning of maritime vehicles, which partially meets the Convention on the International Regulations (COLREGs) for preventing collisions at sea. To carry out risk assessment with obstacles, one of the decision variables used is the intersection of the Line-of-Sight (LOS) with the obstacle's position. For dynamic obstacles, that position is based on the projection of the obstacle moving forward in time assuming a constant speed and heading. Following a positive risk of collision, a (starboard or portside) manoeuvre is applied. The algorithm is designed to adhere to COLREGs steering rules automatically, in particular, rules 13-16. Unlike using a binary decision variable for risk assessment, which is a common method of choice in the literature, the proposed approach utilises a fuzzy risk index to determine the level of collision risk, minimising the occurrence of false positives. The computational complexity of the proposed algorithm is relatively low making it appealing for real-time implementation. We report encouraging results via simulation analysis for a range of scenarios involving both static and dynamic obstacles.
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14:10-14:30, Paper WeB03.3 | |
Autonomy for Ferries and Harbour Buses: A Collision Avoidance Perspective (I) |
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Enevoldsen, Thomas Thuesen | Technical University of Denmark |
Blanke, Mogens | Technical University of Denmark |
Galeazzi, Roberto | Technical University of Denmark |
Keywords: Autonomous surface vehicles, Trajectory and path planning, Intelligent Transportation Systems
Abstract: This paper provides a collision avoidance perspective to maritime autonomy, in the shift towards Maritime Autonomous Surface Ships (MASS). In particular, the paper presents the developments related to the Greenhoper, Denmark's first autonomous harbour bus. The collision and grounding avoidance scheme, called the Short Horizon Planner (SHP), is described and discussed in detail. Furthermore, the required autonomy stack for facilitating safe and rule-compliant collision avoidance is presented. The inherent difficulties related to adhering to the COLREGs are outlined, highlighting some of the operational constraints and challenges within the space of autonomous ferries and harbour buses. Finally, collision and grounding avoidance is demonstrated using a simulation of the whole Greenhopper autonomy stack.
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14:30-14:50, Paper WeB03.4 | |
Detection and Classification of Man-Made Objects for the Autonomy of Underwater Robots (I) |
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Gentili, Alessandro | University of Pisa |
Bresciani, Matteo | University of Pisa |
Ruscio, Francesco | Università Di Pisa |
Tani, Simone | Università Di Pisa |
Caiti, Andrea | Univ. of Pisa |
Costanzi, Riccardo | Università Di Pisa |
Keywords: Neural networks, Autonomous underwater vehicles, Sensing
Abstract: Recent developments in marine technologies allow underwater vehicles to perform survey missions for data collection in an automatic way. The scientific community is now focusing on endowing these vehicles with strong perception capabilities, aiming at full autonomy and decision-making skills. Such abilities would bring benefits to a wide range of field applications, e.g. Inspection and Maintenance (I&M) of man-made structures, port security, and marine rescue. Indeed, most of these tasks are currently carried out employing remotely operated vehicles, making the presence of humans in water necessary. Projects like Metrological Evaluation and Testing of Robots in International CompetitionS (METRICS), funded by the European Commission, are promoting research on this field by organising events such as the Robotics for Asset Maintenance and Inspection (RAMI) competition. In particular, this competition requires participants to develop perception techniques capable of identifying a set of specific targets. Within such context, this paper presents an algorithm able to detect and classify Objects of Potential Interest (OPIs) in underwater camera images. First, the proposed solution compensates for the quality degradation of underwater images by applying color enhancement and restoration procedures. Then, it exploits deep-learning techniques, as well as color and shape based methods, to recognize and correctly label the predefined OPIs. Preliminary results of the implemented neural network using restored images are provided, and a mean Average Precision (mAP) of about 92% was achieved on the dataset provided to the RAMI competition participating teams by the NATO Science and Technology Organization Centre for Maritime Research and Experimentation (STO CMRE).
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14:50-15:10, Paper WeB03.5 | |
Optimal Positioning of Snake Robots in Vortex Wakes Using Extremum-Seeking Control (I) |
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Orucevic, Amer | Norwegian University of Science and Technology (NTNU) |
Lysø, Mads Erlend Bøe | NTNU |
Schmidt-Didlaukies, Henrik M. | Norwegian University of Science and Technology |
Pettersen, Kristin Y. | Norwegian Univ. of Science and Tech |
Gravdahl, Jan Tommy | Norwegian University of Science and Technology (NTNU) |
Keywords: Nonlinear and optimal marine system control, Autonomous underwater vehicles, Unmanned marine vehicles
Abstract: In this paper we explore the optimal positioning of an underwater snake robot (USR) for energy harvesting in the wake of a bluff body. The USR and fluid are simulated jointly using a coupled vortex particle-mesh method and multi-body system solver. The power dissipated in the damped joints of the robot is used as a proxy for the harvested energy. Furthermore, the effect of different damper coefficients on power dissipation is explored. An extremum-seeking control (ESC) scheme for nonlinear systems with time-varying steady-state solutions is employed to optimize the horizontal placement of the robot. It is found that the dissipated power does have a clear optimum. Moreover, the horizontal position of the USR under the ESC scheme is demonstrated to converge to a vicinity of the optimal position.
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15:10-15:30, Paper WeB03.6 | |
Acoustic Positioning of Multiple AUVs by an ASV: Experimental Validation and Performance Characterisation (I) |
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Bresciani, Matteo | University of Pisa |
Tani, Simone | Università Di Pisa |
Bazzarello, Lorenzo | Università Di Pisa |
Caiti, Andrea | Univ. of Pisa |
Costanzi, Riccardo | Università Di Pisa |
Keywords: Acoustic-based networked control and navigation, Marine system navigation, guidance and control, Unmanned marine vehicles
Abstract: Cooperation among heterogeneous marine vehicles can offer several benefits to underwater applications, such as supporting the navigation of submerged robots by leveraging the information available to a surface vehicle. Within such context, this paper describes an acoustic positioning and communication protocol developed for the localisation of multiple Autonomous Underwater Vehicles (AUVs) by means of an Autonomous Surface Vehicle (ASV) equipped with an Ultra-Short BaseLine (USBL) device. To avoid packet collisions, access to the acoustic channel is managed through a time slot division mechanism. Unlike a classical Time Division Multiple Access (TDMA) protocol, the approach considered in this work consists of a centralised scheduling handled by the ASV, in which AUVs are localised at regular time epoch but can transmit only when queried. This allows to prioritise the number of position measurements taken by the ASV and then relayed back to the submerged vehicles, with the final goal of improving the navigation accuracy of the latter. The solution is also designed to handle the latency of acoustic communication and to correctly associate each position measurement with the corresponding acquisition time. Furthermore, it does not require any a priori synchronisation between the clocks of the vehicles involved and ensures complete decoupling between their navigation algorithms. Experimental activities in very-shallow waters, involving an ASV and two target nodes, were carried out to validate the multi-AUVs positioning system and to provide a characterisation of its performance.
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WeB04 |
Room 303 |
Recent Advances in Automated Learning and Calibration of MPC Policies |
Open Invited Session |
Chair: Krishnamoorthy, Dinesh | Eindhoven University of Technology |
Co-Chair: Mesbah, Ali | University of California, Berkeley |
Organizer: Krishnamoorthy, Dinesh | Eindhoven University of Technology |
Organizer: Mesbah, Ali | University of California, Berkeley |
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13:30-13:50, Paper WeB04.1 | |
Learning Safety in Model-Based Reinforcement Learning Using MPC and Gaussian Processes (I) |
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Airaldi, Filippo | Delft University of Technology |
De Schutter, Bart | Delft University of Technology |
Dabiri, Azita | Delft University of Technology |
Keywords: Data-driven optimal control, Predictive control
Abstract: This paper proposes a method to encourage safety in Model Predictive Control (MPC)-based Reinforcement Learning (RL) via Gaussian Process (GP) regression. The framework consists of 1) a parametric MPC scheme that is employed as model-based controller with approximate knowledge on the real system’s dynamics, 2) an episodic RL algorithm tasked with adjusting the MPC parametrization in order to increase its performance, and 3) GP regressors used to estimate, directly from data, constraints on the MPC parameters capable of predicting, up to some probability, whether the parametrization is likely to yield a safe or unsafe policy. These constraints are then enforced onto the RL updates in an effort to enhance the learning method with a probabilistic safety mechanism. Compared to other recent publications combining safe RL with MPC, our method does not require further assumptions on, e.g., the prediction model in order to retain computational tractability. We illustrate the results of our method in a numerical example on the control of a quadrotor drone in a safety-critical environment.
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13:50-14:10, Paper WeB04.2 | |
Sobolev Training for Data-Efficient Approximate Nonlinear MPC (I) |
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Lüken, Lukas | TU Dortmund University |
Brandner, Dean | TU Dortmund University |
Lucia, Sergio | TU Dortmund University |
Keywords: Predictive control, Data-driven optimal control
Abstract: Model predictive control is a powerful advanced control technique to deal with complex nonlinear systems with constraints. Despite recent advances in computing hardware and optimization algorithms, solving the nonconvex optimization problems associated to nonlinear model predictive control in real time can still be intractable. There are several possibilities to alleviate the challenge of computational complexity. An increasingly popular approach is to use neural networks to approximate the mapping between current system state and the corresponding optimal control input, which is implicitly defined by an optimization problem. These approaches typically need a large amount of data. Although the data can be generated offline by sampling the state space and solving many model predictive control problems in advance, it can become intractable especially for increasing system dimensions. In this work, we propose to use the parametric sensitivities of the nonlinear optimization problems as additional information that is provided to the neural network during training. In this way, the neural network not only fits the solution of the optimization problems itself but also its gradients. This training method, usually called Sobolev training, can lead to a higher accuracy in the approximation for the same amount of data. We illustrate the potential of the approach with a simulation study of a nonlinear chemical reactor.
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14:10-14:30, Paper WeB04.3 | |
Reinforcement Learning for MPC: Fundamentals and Current Challenges (I) |
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Bahari Kordabad, Arash | Norwegian University of Science and Technology |
Reinhardt, Dirk Peter | Norwegian University of Science and Technology |
Anand, Akhil | Norwegian University of Science and Technology (NTNU) |
Gros, Sebastien | NTNU |
Keywords: Data-driven optimal control, Predictive control, Data-driven robust control
Abstract: Recent publications have laid a solid theoretical foundation for the combination of Reinforcement Learning and Model Predictive Control, in view of obtaining high-performance data-driven MPC policies. Early practical results, both in simulation and in experiments, have shown the potential of this combination but have also revealed certain challenges. In addition, the technical complexity of these results makes it difficult for interested readers to gather the fundamental ideas and principles behind this combination. This paper aims to provide a coherent and more accessible picture of these results and to offer significantly deeper and more mature insights into their meaning than has been proposed before. It also aims at identifying the current challenges in the field.
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14:30-14:50, Paper WeB04.4 | |
On Tuning Parameterized Control Policies Online for Safety-Critical Systems - Applied to Biomedical Systems (I) |
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Krishnamoorthy, Dinesh | Eindhoven University of Technology |
Keywords: Predictive control, Data-driven optimal control, Nonlinear predictive control
Abstract: There are different approaches to tune a control policy that would result in a desired closed-loop performance. The typical design flow involves tuning the control policies offline using (high-fidelity) simulators until satisfactory performance is achieved. This paper on the other hand, considers the problem of tuning parameterized control policies directly by interacting with the real system that also has safety-critical constraints. We use safe Bayesian optimization using interior-point methods to tune the parameters online that guarantees constraint satisfaction with high probability. The proposed framework is applied to a personalized artificial pancreas system for type 1 diabetes. The paper shows that the parameterized control policy used for blood glucose regulation can be safely tuned to personalize the controller for each individual patient using our approach and thus improve its performance.
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14:50-15:10, Paper WeB04.5 | |
Practical Considerations in Reinforcement Learning-Based MPC for Mobile Robots (I) |
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Busetto, Riccardo | Politecnico Di Milano |
Breschi, Valentina | Eindhoven University of Technology |
Vaccari, Giulio | Politecnico Di Milano |
Formentin, Simone | Politecnico Di Milano |
Keywords: Data-based control, Parametric optimization
Abstract: In mobile robot applications, the trajectory tracking task hides several difficulties, including the choice of the setpoint and the search for an acceptable trade-off between performance and computational constraints. In this work, we discuss practical issues of a Reinforcement Learning (RL) based Model Predictive Control (MPC) tuning approach by focusing on a specific mobile robot application, where the objective is to maximize the velocity, while keeping the robot within the track bounds. Among others, we show that softening the latter constraints allows us to obtain a RL-tuned tracking controller with the same performance of an economic nonlinear MPC formulation, but requiring significantly less computational resources.
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15:10-15:30, Paper WeB04.6 | |
Automated Loading Operation for Mass-Production Hydraulic Excavators by Nonlinear Model Predictive Control (I) |
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Ishihara, Shinji | Hitachi, Ltd., Research & Development Group |
Narikawa, Ryu | Hitachi, Ltd |
Ohtsuka, Toshiyuki | Kyoto University |
Keywords: Nonlinear predictive control, Parametric optimization, Data-driven optimal control
Abstract: This study deals with the control methods for automation of the loading operation of hydraulic excavators for mass production. In the loading operation, it is necessary to move the bucket to the target position without spilling soil from the bucket. Since the loading operation is a combined operation of the front equipment and the swing operation, it is not easy to generate the ideal trajectory. We apply Model Predictive Control (MPC) to this problem and investigate a method to realize ideal loading operation by giving only the coordinates of the loading position. When using MPC, the challenge is that a lot of worker-hours are spent on tuning the weights of the objective function. We also propose an efficient weight tuning method to solve this problem, with a view to adapting it to hydraulic excavators for mass production. We have confirmed the effectiveness of the proposed method through numerical simulations.
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WeB05 |
Room 304 |
Robustness Analysis |
Regular Session |
Chair: Scherer, Carsten W. | Department of Mathematics, University of Stuttgart |
Co-Chair: Hara, Shinji | Tokyo Institute of Technology |
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13:30-13:50, Paper WeB05.1 | |
Robust Exponential Stability and Invariance Guarantees with General Dynamic O'Shea-Zames-Falb Multipliers |
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Scherer, Carsten W. | Department of Mathematics, University of Stuttgart |
Keywords: Robustness analysis, Convex optimization, Uncertain systems
Abstract: We propose novel time-domain dynamic integral quadratic constraints with a terminal cost for exponentially weighted slope-restricted gradients of not necessarily convex functions. This extends recent results for subdifferentials of convex function and their link to so-called O'Shea-Zames-Falb multipliers. The benefit of merging time-domain and frequency-domain techniques is demonstrated for linear saturated systems.
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13:50-14:10, Paper WeB05.2 | |
On Phase Change Rate Maximization with Practical Applications |
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Kao, Chung-Yao | National Sun Yat-Sen University |
Hara, Shinji | Tokyo Institute of Technology |
Hori, Yutaka | Keio University |
Iwasaki, Tetsuya | UCLA |
Khong, Sei Zhen | - |
Keywords: Robustness analysis, System analysis and optimization
Abstract: We recapitulate the notion of phase change rate maximization and demonstrate the usefulness of its solution on analyzing the robust instability of a cyclic network of multi-agent systems subject to a homogenous multiplicative perturbation. Subsequently, we apply the phase change rate maximization result to two practical applications. The first is a magnetic levitation system, while the second is a repressilator with time-delay in synthetic biology.
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14:10-14:30, Paper WeB05.3 | |
Analysis of Aperiodic Sampled Data Lur’e Systems Using Integral Quadratic Constraints |
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Turner, Matthew C. | University of Southampton |
Gomes Da Silva Jr, Joao Manoel | Universidade Federal Do Rio Grande Do Sul (UFRGS) |
Keywords: Robustness analysis, Stability of nonlinear systems, Robust linear matrix inequalities
Abstract: This paper considers the stability analysis of a class of sampled data Lur'e systems with possibly aperiodic sampling times. The analysis conditions are formulated in an IQC framework where i) the nonlinear component, as usual, is modelled using sector and slope restrictions which have well-known integral quadratic constraints associated with them; and ii) the sample-and-hold operator is represented, after loop transformations as an operator which satisfies certain other integral quadratic constraints. The arising analysis conditions can then be expressed as a frequency domain condition and a time domain constraint. Under various assumptions these can be transformed into linear matrix inequality conditions. Quite logically, when the bound on the sample interval tends to zero, the continuous time stability conditions for Lur'e systems are recovered.
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14:30-14:50, Paper WeB05.4 | |
Input-Output-Data-Enhanced Robust Analysis Via Lifting |
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Holicki, Tobias | University of Stuttgart |
Scherer, Carsten W. | Department of Mathematics, University of Stuttgart |
Keywords: Robustness analysis, Data-driven robust control, Robust linear matrix inequalities
Abstract: Starting from a linear fractional representation of a linear system affected by constant parametric uncertainties, we demonstrate how to enhance standard robust analysis tests by taking available (noisy) input-output data of the uncertain system into account. Our approach relies on lifting the system and the construction of data-dependent multipliers. It leads to a test in terms of linear matrix inequalities which guarantees stability and performance for all systems compatible with the observed data if it is in the affirmative. In contrast to many other data-based approaches, prior physical or structural knowledge about the system can be incorporated at the outset by exploiting the power of linear fractional representations.
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14:50-15:10, Paper WeB05.5 | |
A Variant of Extended LMI: Performance Analysis with Static Multiplier for Discrete-Time Lifted Systems |
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Sato, Masayuki | Kumamoto University |
Sebe, Noboru | Kyushu Institute of Technology |
Keywords: Robustness analysis, Uncertain systems, Convex optimization
Abstract: This note revisits extended Linear Matrix Inequality (LMI) formulation of performance analysis, which incorporates static multiplier, for parametrically multi-affine discrete-time Linear Time-Invariant Parameter-Dependent (LTIPD) and Linear Periodically Time-Varying (LPTV) systems using lifting technique. Almost the same analysis conditions for parametrically affine discrete-time LTIPD/LPTV systems as the ones shown in this note have already been proposed in the literature, we thus focus on the simple derivations of the conditions using only Elimination lemma. To this end, a variant of extended LMI formulation, whose dimensional sizes are slightly larger than the conventional formulation with additional auxiliary matrices, is proposed in this note. It is also shown that our derived variant directly leads to a parametrically multi-affine extended LMI formulation for our addressed problem.
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15:10-15:30, Paper WeB05.6 | |
Robustness Analysis of Nonlinear Systems Along Uncertain Trajectories |
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Biertümpfel, Felix | Technische Universität Dresden |
Theis, Julian | Airbus Defence and Space |
Pfifer, Harald | Technische Universität Dresden |
Keywords: Robustness analysis, Time-varying systems, Uncertain systems
Abstract: The paper presents a novel approach for robustness analysis of nonlinear dynamic systems in the vicinity of a reference trajectory. The approach linearizes the system with respect to a nominal trajectory and calculates a guaranteed upper bound on the worst-case gain. In contrast to existing methods rooted in linear time-varying systems analysis, the approach accurately includes perturbations that drive the system away from the reference trajectory. The approach further includes a bound for the error associated with the time-varying linearization. Hence, the results obtained in the linear framework provide a valid upper bound for the worst-case performance of the nonlinear system. The calculation of the upper bound relies on the dissipation inequalities formulated in the framework of integral quadratic constraints. It is therefore computationally much cheaper than sample-based methods such as Monte Carlo simulation. The feasibility of the approach is demonstrated on a numerical example.
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WeB06 |
Room 311 |
Nonlinear System Identification II |
Regular Session |
Chair: McKelvey, Tomas | Chalmers University of Technology |
Co-Chair: Bokor, Jozsef | Hungarian Academy of Sciences |
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13:30-13:50, Paper WeB06.1 | |
Order Selection for Stochastic Bilinear Systems |
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Bokor, Jozsef | Hungarian Academy of Sciences |
Terdik, György | University of Debrecen |
Keywords: Nonlinear system identification, Frequency domain identification, Stochastic system identification in signal processing
Abstract: Identification of bilinear systems subject to white inputs is studied. Assuming bilinearity we use the crosscovariances between the output and the higher order Hermite polynomials of the input for estimating the coefficients of the Hermite series expansion of the output. The parameters of the bilinear model are obtained via a balanced factorization of the appropriately constructed Hankel matrix. The skewness of the singular values of the estimated Hankel matrix is applied for testing the order selection for the bilinear model.
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13:50-14:10, Paper WeB06.2 | |
On the Validity of Using the Delta Method for Calculating the Uncertainty of the Predictions from an Overparameterized Model |
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Malmström, Magnus | Linköping University |
Skog, Isaac | KTH |
Axehill, Daniel | Linköping University |
Gustafsson, Fredrik | Linköping University |
Keywords: Machine learning, Nonlinear system identification, Autonomous vehicles
Abstract: The uncertainty in the prediction calculated using the delta method for an overparameterized (parametric) black-box model is shown to be larger or equal to the uncertainty in the prediction of a canonical (minimal) model. Equality holds if the additional parameters of the overparameterized model do not add flexibility to the model. As a conclusion, for an overparameterized black-box model, the calculated uncertainty in the prediction by the delta method is not underestimated. The results are shown analytically and are validated in a simulation experiment where the relationship between the normalized traction force and the wheel slip of a car is modelled using e.g., a neural network.
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14:10-14:30, Paper WeB06.3 | |
Density Estimation in the Regressor Space for Nonlinear System Identification |
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Peter, Timm Julian | University of Siegen |
Kösters, Tarek | University of Siegen |
Nelles, Oliver | University of Siegen |
Keywords: Nonlinear system identification, Machine learning, Modeling and control of agriculture
Abstract: In this paper, the functioning and performance of a recently proposed weighting approach for dynamic datasets is demonstrated for nonlinear system identification. The overall goal of the new method is to improve data-driven model performance. This is achieved by increasing the weight of training data points in areas of the regressor space that are underrepresented during training, while decreasing the weight for overrepresented data points. The method is based on estimating the parameters of a model using weighted error norms, where the weighting is carried out with the inverse values of the kernel density estimated in the regressor space. The performance of the new method is investigated using nonlinear ARX models for the identification of (i) an artificial Hammerstein process and (ii) a nonlinear real-world process. Overall, the new weighting method shows significantly improved performance on the simulation error. It is demonstrated that performance is improved most notably in areas that are underrepresented in the training data.
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14:30-14:50, Paper WeB06.4 | |
Physically Consistent Neural ODEs for Learning Multi-Physics Systems |
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Zakwan, Muhammad | EPFL, Switzerland |
Di Natale, Loris | Empa / EPFL |
Svetozarevic, Bratislav | Swiss Federal Laboratories for Materials Science and Technology |
Heer, Philipp | Empa, Urban Energy Systems |
Jones, Colin, N | EPFL |
Ferrari-Trecate, Giancarlo | Ecole Polytechnique Fédérale De Lausanne |
Keywords: Nonlinear system identification, Machine learning in modelling, prediction, control and automation, Time series modelling
Abstract: Despite the immense success of neural networks in modeling system dynamics from data, they often remain physics-agnostic black boxes. In the particular case of physical systems, they might consequently make physically inconsistent predictions, which makes them unreliable in practice. In this paper, we leverage the framework of Irreversible port-Hamiltonian Systems (IPHS), which can describe most multi-physics systems, and rely on Neural Ordinary Differential Equations (NODEs) to learn their parameters from data. Since IPHS models are consistent with the first and second principles of thermodynamics by design, so are the proposed Physically Consistent NODEs (PC-NODEs). Furthermore, the NODE training procedure allows us to seamlessly incorporate prior knowledge of the system properties in the learned dynamics. We demonstrate the effectiveness of the proposed method by learning the thermodynamics of a building from the real-world measurements and the dynamics of a simulated gas-piston system. Thanks to the modularity and flexibility of the IPHS framework, PC-NODEs can be extended to learn physically consistent models of multi-physics distributed systems
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14:50-15:10, Paper WeB06.5 | |
Iteratively-Linearized Set-Based Parameter Estimation for Uncertain Nonlinear Systems |
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Ito, Yuji | Toyota Central R&d Labs., Inc |
Keywords: Grey box modelling, Nonlinear system identification, Continuous time system estimation
Abstract: This study presents a set-based method to estimate unknown parameters of continuous-time structured nonlinear systems under uncertainties. Sets containing the parameters are found by using data sets and structures of the systems. Such estimation is challenging because the uncertainties are caused by disturbances, data noises, and partially unknown dynamics. In addition, the estimation for continuous-time nonlinear systems faces nonlinear problems that are difficult to address. To overcome these issues, the proposed set-based method solves linear programming (LP) problems iteratively instead of the nonlinear problems. The inequalities in the LP are derived such that they are consistent with the true parameters, using the boundedness of the uncertainties. A theoretical analysis guarantees that solving the iterative LP gives sets containing the true parameters.
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15:10-15:30, Paper WeB06.6 | |
Analysis of Interpolating Regression Models and the Double Descent Phenomenon |
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McKelvey, Tomas | Chalmers University of Technology |
Keywords: Machine learning, Nonlinear system identification, Estimation theory
Abstract: A regression model with more parameters than data points in the training data is overparametrized and has the capability to interpolate the training data. Based on the classical bias-variance tradeoff expressions, it is commonly assumed that models which interpolate noisy training data are poor to generalize. In some cases, this is not true. The best models obtained are overparametrized and the testing error exhibits the double descent behavior as the model order increases. In this contribution, we provide some analysis to explain the double descent phenomenon, first reported in the machine learning literature. We focus on interpolating models derived from the minimum norm solution to the classical least-squares problem and also briefly discuss model fitting using ridge regression. We derive a result based on the behavior of the smallest singular value of the regression matrix that explains the peak location and the double descent shape of the testing error as a function of model order.
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WeB07 |
Room 312 |
Identification, Learning and Control of Quantum Systems II |
Open Invited Session |
Chair: Ohki, Kentaro | Kyoto University |
Co-Chair: Petersen, Ian R | The Australian National University |
Organizer: Dong, Daoyi | University of New South Wales |
Organizer: Li, Jr-Shin | Washington University in St. Louis |
Organizer: Qi, Bo | Chinese Academy of Scineces |
Organizer: Petersen, Ian R | The Australian National University |
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13:30-13:50, Paper WeB07.1 | |
Tomography of Quantum Detectors Using Neural Networks (I) |
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Ma, Hailan | The University of New South Wales |
Xiao, Shuixin | Shanghai Jiao Tong University |
Dong, Daoyi | University of New South Wales |
Petersen, Ian R | The Australian National University |
Keywords: Machine learning, Closed loop identification
Abstract: Quantum detector tomography is a fundamental technique for calibrating quantum devices and thus lay foundations for quantum information processing tasks. In this work, we propose a quantum detector tomography method that employs deep neural networks to reconstruct quantum detectors from a set of probe states with high efficiency. Numerical results demonstrate that the proposed method exhibits a significant potential to estimate phase-insensitive detectors.
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13:50-14:10, Paper WeB07.2 | |
Quantum State and Detector Tomography with Known Rank (I) |
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Xiao, Shuixin | Shanghai Jiao Tong University |
Wang, Yuanlong | Griffith University |
Zhang, Jun | Shanghai Jiao Tong University |
Dong, Daoyi | University of New South Wales |
Yonezawa, Hidehiro | University of New South Wales |
Keywords: Closed loop identification, Continuous time system estimation
Abstract: Quantum state tomography and quantum detector tomography are two main problems in quantum system identification. In this paper, we study state tomography and detector tomography with prior knowledge about the true rank of the unknown state/detector. In this case, we propose a sufficient condition for non-adaptive tomography algorithms to achieve the optimal infidelity scaling O(1/N) on the number of state copies N . Then we present two examples of such non-adaptive quantum state tomography and quantum detector tomography algorithms. Numerical examples demonstrate the effectiveness of our algorithms.
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14:10-14:30, Paper WeB07.3 | |
Learning Quantum Distributions with Variational Diffusion Models (I) |
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Wang, Yong | Tongji University |
Cheng, Shuming | Tongji University |
Li, Li | College of Electronic and Information Engineering, Tongji Univer |
Chen, Jie | Beijing Institue of Technology |
Keywords: Machine learning
Abstract: It is challenging to identify the state of many-body quantum systems, as recovering density matrices underlying the quantum state typically requires computational resources scale exponentially to the system size. In this work, we introduce the variational diffusion model (VDM) to efficiently learn high-dimensional quantum distributions with high fidelity, which is essential to realize the fast reconstruction of quantum states. We build up the VDM suitable for dealing with the high-dimensional quantum samples, and then perform numerical experiments to test our model and other autoregressive models, including recurrent neural network and transformer. It is found that the VDM can achieve a modest better performance with fewest parameters than other two to learn the distribution as desired. Our results pave the way to applying diffusion models to solve hard problems in the quantum domain.
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14:30-14:50, Paper WeB07.4 | |
Finitely Repeated Adversarial Quantum Hypothesis Testing |
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Hu, Yinan | New York University |
Zhu, Quanyan | New York University |
Keywords: Fault detection and diagnosis, Control of quantum and Schroedinger systems
Abstract: Quantum technologies have been considered as a method to enhance cyber-security due to the unique properties of quantum systems. However, quantum systems themselves could also suffer from strategic attacks. In this paper, we formulate the relationship between the strategic attacker and a passive quantum detector into a Stackelberg game. By deriving the optimal detection rule at equilibrium, we study the detection performance of the detector under the setting of finite sample size of corrupted observations. Under mild assumptions, we show that the miss. We illustrate the general decaying results of the miss rate numerically, depicting that the passive detector manages to achieve a miss rate and a false alarm rate both exponentially decaying to zero given infinitely many quantum states, although at a much slower rate than a quantum non-adversarial counterpart. Finally, we adopt our formulations upon a case study of detection with quantum radars.
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14:50-15:10, Paper WeB07.5 | |
Optimal Discrete Heat Distribution Using the Quantum Approximate Optimization Algorithm |
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Abdul Rahman, Salahuddin | Aalborg University |
Thorsteinsson, Simon | Aalborg University |
Clausen, Henrik Glavind | Aalborg University |
Karabacak, Ozkan | Aalborg University |
Wisniewski, Rafal | Aalborg University |
Keywords: Large scale optimization problems, Control of quantum and Schroedinger systems, Control of heat and mass transfer systems
Abstract: In this work, a discrete heat distribution (DHD) problem is formulated and solved using the quantum approximate optimization algorithm (QAOA). The goal of the DHD problem is to suggest a reasonable valve configuration that finds a compromise between room temperature comfort and desired water flow. The DHD problem is formulated as an integer quadratic programming (IQP) problem, which is an NP-hard combinatorial optimization problem. For a large number of decision variables, this problem becomes computationally intractable to be solved for an exact solution and rather an approximate solution is favorable, making QAOA a potential candidate to solve this problem. For the DHD problem to be solved using the QAOA, it is converted first to a quadratic unconstrained binary optimization (QUBO) problem. The algorithm is implemented and simulated for various circuit depths and tested on IBM quantum computer. The results show that the algorithm can solve the problem for low circuit depths. This paper aims at showing a use case of NISQ devices in control engineering and suggests new applications of the QAOA in the design of controllers for dynamical systems.
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15:10-15:30, Paper WeB07.6 | |
On Faster Convergence of Stochastic Approximation for Adaptive Quantum Control |
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Ohki, Kentaro | Kyoto University |
Enami, Shoju | Kyoto University |
Keywords: Stochastic adaptive control, Stochastic control, Control of quantum and Schroedinger systems
Abstract: Fast learning of uncertain parameters is crucial for control performance of adaptive control. This paper proposes two optimization problems for stochastic approximation and discusses a faster convergence rate of adaptive control for a class of stochastic systems based on the optimal solution. Under a specific condition, we derive the optimal adaptive gain explicitly and discuss how faster convergence of a state for an adaptive quantum control problem achieves based on the optimal adaptive gain.
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WeB08 |
Room 313 |
Distributed Optimization for Large-Scale Systems II |
Regular Session |
Chair: Guay, Martin | Queen's Univ |
Co-Chair: Gusrialdi, Azwirman | Tampere University |
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13:30-13:50, Paper WeB08.1 | |
Distributed Optimization with Gradient Descent and Quantized Communication |
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Rikos, Apostolos I. | KTH Royal Institute of Technology |
Jiang, Wei | School of Electrical Engineering, Aalto University, Finland |
Charalambous, Themistoklis | University of Cyprus |
Johansson, Karl H. | KTH Royal Institute of Technology |
Keywords: Distributed optimization for large-scale systems, Quantized control, Distributed control and estimation
Abstract: In this paper, we consider the unconstrained distributed optimization problem, in which the exchange of information in the network is captured by a directed graph topology, thus, nodes can only communicate with their neighbors. Additionally, in our problem, the communication channels among the nodes have limited bandwidth. In order to alleviate this limitation, quantized messages should be exchanged among the nodes. For solving this distributed optimization problem, we combine a gradient descent method with a distributed quantized consensus algorithm (which requires the nodes to exchange quantized messages and converges in a finite number of steps). Specifically, at every optimization step, each node (i) performs a gradient descent step (i.e., subtracts the scaled gradient from its current estimate), and (ii) performs a finite-time calculation of the quantized average of every node’s estimate in the network. As a consequence, this algorithm approximately mimics the centralized gradient descent algorithm. We show that our algorithm asymptotically converges to a neighborhood of the optimal solution with linear convergence rate. The performance of the proposed algorithm is demonstrated via simple illustrative examples.
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13:50-14:10, Paper WeB08.2 | |
Resilient Design of Continuous-Time Distributed Optimization Algorithm in the Presence of Cyber-Attacks |
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Iqbal, Muhammad | Tampere University |
Qu, Zhihua | University of Central Florida |
Gusrialdi, Azwirman | Tampere University |
Keywords: Distributed optimization for large-scale systems, Security in networked control systems, Distributed control and estimation
Abstract: This paper presents a continuous-time resilient distributed optimization algorithm based on competitive interaction design method on connected graphs in the presence of adversaries. The competitive interaction method allows us to design a network that protects the multi-agent systems from adversaries without requiring high network connectivity. In addition, the proposed algorithm does not require the global information about the number of adversaries. First, we show that the proposed distributed algorithm solves the resilient distributed optimization problem with no attack on the communication links. Second, we show that the proposed continuous-time distributed optimization algorithm on connected graphs converges to the small neighborhood of the optimal solution in the presence of cyber-attacks onto the communication channel. Simulations are presented to illustrate our theoretical results.
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14:10-14:30, Paper WeB08.3 | |
A Random Memory Length Adaptive Algorithm for Vertex Cover Problem |
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Niu, Shaoyuan | Tongji University |
Li, Xiang | Tongji University |
Keywords: Distributed optimization for large-scale systems, Game theories, Graph-based methods for networked systems
Abstract: The vertex cover (VC) problem has been studied for past few years, and some centralized and distributed algorithms have been proposed. In this paper, we propose the so-called random memory length adaptive (RMLA) algorithm for the VC problem in networks. Any initial state can reach the stable pure strict Nash equilibrium state through finite iterations by the RMLA algorithm. We find that by setting the minimum edge-keeping probability reasonably, the convergence rapidity and accuracy can be improved simultaneously. Our algorithm also removes the requirement for consistent node memory length. Through theoretical analysis and intensive numerical simulations, we verify the convergence and effectiveness of the RMLA algorithm.
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14:30-14:50, Paper WeB08.4 | |
A Novel Decentralized Approach to Large-Scale Multi-Agent MILPs |
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Manieri, Lucrezia | Politecnico Di Milano |
Falsone, Alessandro | Politecnico Di Milano |
Prandini, Maria | Politecnico Di Milano |
Keywords: Distributed optimization for large-scale systems, Large scale optimization problems, Smart grids
Abstract: We address the optimal operation of a large-scale multi-agent system where agents have to set their own continuous and/or discrete decision variables so as to jointly minimize the sum of local linear performance indices while satisfying local and global linear constraints. When the number of discrete decision variables is large, solving the resulting Mixed Integer Linear Program becomes computationally demanding, and often impossible in practice. Inspired by some recent methods in the literature, we propose a decentralized iterative scheme that recovers computational tractability by decomposing the dual of the MILP problem into lower-dimensional MILPs, one per agent, and obtains feasibility of the recovered primal solution by introducing a fictitious tightening of the global constraints. The tightening is updated in an adaptive fashion according to an heuristic strategy which allows it to both increase and decrease throughout the iterations, depending on the mismatch between the recovered mixed-integer primal solution and the solution to the relaxed linear problem associated with the current tightening. The procedure is shown to be effective and to outperform state-of-the-art alternative resolution schemes in a benchmark example on optimal charging of a fleet of electric vehicles.
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14:50-15:10, Paper WeB08.5 | |
Distributed Optimization by Newton Consensus Over Connected Digraphs |
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Guay, Martin | Queen's Univ |
Keywords: Distributed optimization for large-scale systems, Consensus, Multi-agent systems
Abstract: In this study, a Newton consensus method is proposed for the distributed optimization of a multi-agent systems operating over strongly connected digraphs. The approach proposes an approximate Newton step for both the primal and dual problems that can be implemented in a completely decentralized fashion. The asymmetry in the communication network is addressed by computing an approximate Newton step that only requires the out-Laplacian. The proposed Newton consensus approach does not require the exchange of derivative information between agents. In addition, the optimization approach avoids the explicit inversion of the approximate Hessian information for the computation of the Newton step. A simulation study demonstrates the effectiveness of the technique.
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15:10-15:30, Paper WeB08.6 | |
Distributed Asynchronous Large-Scale Mixed-Integer Linear Programming Via Saddle Point Computation |
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Fina, Luke | University of Florida |
Hale, Matthew | University of Florida |
Keywords: Distributed optimization for large-scale systems, Multi-agent systems
Abstract: We solve large-scale mixed-integer linear programs (MILPs) via distributed asynchronous saddle point computation. To solve a MILP, we relax it with a nonlinear program approximation whose accuracy tightens as the number of agents increases relative to the number of coupled constraints. Next, we form an equivalent Lagrangian saddle point problem, and create a regularized Lagrangian that is strongly-convex-strongly-concave. We then develop a parallelized algorithm to compute saddle points of the regularized Lagrangian. This algorithm partitions problems into blocks and it is shown to tolerate asynchrony in the computations and communications of primal and dual variables. Suboptimality bounds and convergence rates are presented for convergence to a saddle point. The suboptimality bound includes (i) the regularization error induced by regularizing the Lagrangian and (ii) the suboptimality gap between solutions to the original MILP and its relaxed form. Simulation results illustrate these theoretical developments in practice, and show that relaxation and regularization together have only a mild impact on the quality of solution obtained.
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WeB09 |
Room 314 |
Estimation and Filtering I |
Regular Session |
Chair: Yan, Yuyue | Tokyo Institute of Technology |
Co-Chair: Ruderman, Michael | University of Agder |
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13:30-13:50, Paper WeB09.1 | |
Robust Asymptotic Observer of Motion States with Nonlinear Friction |
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Ruderman, Michael | University of Agder |
Keywords: Estimation and filtering, Identification for control, Mechanical and aerospace estimation
Abstract: This paper revisits the previously proposed linear asymptotic observer of the motion state variables with nonlinear friction and provides a robust design suitable for both, transient presliding and steady-state sliding phases of the relative motion. The class of motion systems with the only measurable output displacement is considered. The reduced-order Luenberger-type observer is designed based on the obtained simplified state-space representation with a time-varying system matrix. The resulted observation error dynamics proves to be robust and appropriate for all variations of the system matrix, which are due to the nonlinear spatially-varying friction. A specially designed tribological setup to accurately monitor the relative motion between two contacting friction surfaces is used to collect the experimental data of the deceleration trajectories when excited by a series of impulses. The performance of the state estimation using the proposed observer is shown based on the collected experimental data.
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13:50-14:10, Paper WeB09.2 | |
Efficient Point Mass Predictor for Continuous and Discrete Models with Linear Dynamics |
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Matousek, Jakub | University of West Bohemia |
Dunik, Jindrich | University of West Bohemia |
Brandner, Marek | University of West Bohemia |
Park, Chan Gook | Seoul National Univ |
Choe, Yeongkwon | Korea Electronics Technology Institute |
Keywords: Estimation and filtering, Estimation theory, Bayesian methods
Abstract: This paper deals with state estimation of stochastic models with linear state dynamics, continuous or discrete in time. The emphasis is laid on a numerical solution to the state prediction by the time-update step of the grid-point-based point-mass filter (PMF), which is the most computationally demanding part of the PMF algorithm. A novel way of manipulating the grid, leading to the time-update in form of a convolution, is proposed. This reduces the PMF time complexity from quadratic to log-linear with respect to the number of grid points. Furthermore, the number of unique transition probability values is greatly reduced causing a significant reduction of the data storage needed. The proposed PMF prediction step is verified in a numerical study.
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14:10-14:30, Paper WeB09.3 | |
Stochastic Differential Equations with State Dependent Diffusion - 2 Order Statistics and State Estimation |
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Knudsen, Torben | Aalborg University |
Keywords: Estimation and filtering, Stochastic system identification, Continuous time system estimation
Abstract: Estimation of states in stochastic differential equations with state dependent diffusion is known to be difficult. Previous research recommend the higher order extended Kalman filter or the Lamperti transform method for this case. This paper shows that a new developed method, based on the unscented Kalman filter, is superior for two simulated stochastic differential equation systems.
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14:30-14:50, Paper WeB09.4 | |
The Simple Solution for Nonlinear State Estimation of Ill-Conditioned Systems: The Normalized Unscented Kalman Filter |
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Krog, Halvor Aarnes | Norwegian University of Science and Technology |
Jäschke, Johannes | Norwegian University of Science & Technology |
Keywords: Estimation and filtering, Kalman Filtering, Estimation theory
Abstract: An easy-to-implement method for nonlinear state estimation for ill-conditioned systems is proposed. By propagating standard deviations and correlations instead of the covariance in the unscented Kalman filter (UKF), the condition numbers of relevant matrices are reduced. The reduction in the condition number is related to the scaling of the problem. Hence, what we propose is a normalization method that acts as an “auto-scaler”. Compared to other methods in state estimation for ill-conditioned systems, our proposed method factors the covariance matrix into physically meaningful statistics which can be used to check for filter divergence online. The method is compared to a standard UKF in a case study and shows a significant reduction in the condition number.
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14:50-15:10, Paper WeB09.5 | |
A Generalized GraphEM for Sparse Time-Varying Dynamical Systems |
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Greiff, Carl Marcus | Mitsubishi Electric Research Laboratories |
Di Cairano, Stefano | Mitsubishi Electric Research Laboratory |
Mansour, Hassan | MERL |
Berntorp, Karl | Mitsubishi Electric Research Labs |
Keywords: Estimation and filtering, Kalman Filtering, Stochastic system identification
Abstract: We consider the problem of joint parameter estimation and smoothing in structured linear systems using the expectation maximization (EM) framework. Specifically, we explore how partially known sparsity structures in the estimation model can be leveraged to improve the computation speed and performance of the considered EM approaches. We use these ideas to generalize a recently proposed GraphEM algorithm to a linear time-varying setting, where the sparsity structures may vary in time. We obtain a biconvex form of the majorizing function in the M-step, which is minimized subject to an l1-regularization using a Douglas-Rachford proximal splitting algorithm. Numerical results using a satellite positioning example shows significant improvements in the estimation errors and an F1-score that quantifies model sparsity.
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15:10-15:30, Paper WeB09.6 | |
Possibility of Prediction Improvements for Atomic Clock Ensembles: Basis Selection in Undetectable Systems |
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Yan, Yuyue | Tokyo Institute of Technology |
Jensen, Nicholas John | Tokyo Institute of Technology |
Kawaguchi, Takahiro | Gunma University |
Yano, Yuichiro | National Institute of Information and Communications Technology |
Hanado, Yuko | National Institute of Information and Communications Technology |
Ishizaki, Takayuki | Tokyo Institute of Technology |
Keywords: Estimation and filtering, Linear systems, Infrastructure (including energy, telecoms, political, physical, etc.)
Abstract: To generate accurate time scales, such as national standard time in each country and network time in communication systems, a novel prediction algorithm is proposed for the atomic clock ensembles in which the system is unobservable. In the proposed prediction algorithm, to deal with unobservable state space, we consider a steady-state Kalman filter and an intuitive prediction algorithm to separately treat the observable and unobservable state spaces after Kalman canonical decomposition. It turns out that the basis selection plays an important role in affecting prediction performance. We compare the performance of the proposed algorithm with the conventional one and discuss the possibility of prediction improvements by altering the transformation matrix. A couple of numerical examples are presented to illustrate the efficacy of our results.
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WeB10 |
Room 315 |
Event-Triggered and Self-Triggered Control II |
Open Invited Session |
Chair: Takaba, Kiyotsugu | Ritsumeikan University |
Co-Chair: Hirche, Sandra | Technical University of Munich |
Organizer: Heemels, Maurice | Eindhoven University of Technology |
Organizer: Hirche, Sandra | Technical University of Munich |
Organizer: Johansson, Karl H. | KTH Royal Institute of Technology |
Organizer: Malisoff, Michael | Louisiana State Univ |
Organizer: Nowzari, Cameron | George Mason University |
Organizer: Postoyan, Romain | CRAN, CNRS, Université De Lorraine |
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13:30-13:50, Paper WeB10.1 | |
Digital Event-Based Stabilization of Nonlinear Time-Delay Systems (I) |
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Di Ferdinando, Mario | Università Degli Studi Dell'Aquila |
Di Gennaro, Stefano | Univ. Di L'Aquila |
Borri, Alessandro | Istituto Di Analisi Dei Sistemi Ed Informatica "A. Ruberti" (IAS |
Pepe, Pierdomenico | University of L'Aquila |
Keywords: Event-triggered and self-triggered control, Digital implementation, Nonlinear time-delay systems
Abstract: In this paper, the stabilization problem of nonlinear time-delay systems via quantized sampled-data event-based controllers is investigated. Fully nonlinear (i.e., possibly non-affine in the control) systems affected by state delays are studied. Sufficient conditions are provided for the existence of a suitably fast sampling and of an accurate quantization of the input/output channels such that the digital implementation of the continuous-time controller at hand, updated through a proposed event-triggered mechanism, ensures the semi--global practical stability property, with arbitrarily small final target ball of the origin, of the related closed-loop system. A spline approximation methodology is used in order to cope with the problem of the possible non-availability in the buffer of suitable past values of the system variables needed for the digital implementation of the controller. The stabilization in the sample-and-hold sense theory is used as a tool to prove the results. In the theory here developed, the case of non-uniform quantization of the input/output channels and the case of aperiodic sampling are both included. The proposed theoretical results are validated through an application concerning the plasma glucose regulation problem in type-2 diabetic patients.
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13:50-14:10, Paper WeB10.2 | |
Shared Network Effects in Time versus Event-Triggered Consensus of a Single-Integrator Multi-Agent System (I) |
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Meister, David | University of Stuttgart |
Duerr, Frank | University of Stuttgart |
Allgower, Frank | University of Stuttgart |
Keywords: Event-triggered and self-triggered control, Multi-agent systems, Control over networks
Abstract: Event-triggered control has the potential to provide a similar performance level as time-triggered (periodic) control while triggering events less frequently. It therefore appears intuitive that it is also a viable approach for distributed systems to save scarce shared network resources used for inter-agent communication. While this motivation is commonly used also for multi-agent systems, a theoretical analysis of the impact of network effects on the performance of event- and time-triggered control for such distributed systems is currently missing. With this paper, we contrast event- and time-triggered control performance for a single-integrator consensus problem under consideration of a shared communication medium. We therefore incorporate transmission delays and packet loss in our analysis and compare the triggering scheme performance under two simple medium access control protocols. We find that network effects can degrade the performance of event-triggered control beyond the performance level of time-triggered control for the same average triggering rate if the network is used intensively. Moreover, the performance advantage of event-triggered control shrinks with an increasing number of agents and is even lost for sufficiently large networks in the considered setup.
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14:10-14:30, Paper WeB10.3 | |
Cloud-Mediated Self-Triggered Synchronization of Linear Agents Subject to Disturbances (I) |
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Namba, Takumi | Ritsumeikan University |
Takaba, Kiyotsugu | Ritsumeikan University |
Keywords: Event-triggered and self-triggered control, Multi-agent systems, Distributed control and estimation
Abstract: This paper deals with a cloud-mediated self-triggered state synchronization control method of a linear multi-agent system subject to disturbances. In the cloud-mediated self-triggered control approach, each agent asynchronously accesses the cloud repository to get past information on its neighboring agents. Then, the agent predicts the future behavior of its neighbors as well as of its own, and locally determines its next access time to the cloud repository. In this paper, we propose a cloud-mediated state synchronizing controller design method in the presence of disturbances. The uncertainty caused by the disturbances is appropriately handled in the self-triggering rule. It is also proved that the closed-loop system does not exhibit any Zeno behaviors.
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14:30-14:50, Paper WeB10.4 | |
Event-Triggered Pose Synchronization in SE(3) for Cooperating Multi-Robot Teams (I) |
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Budde genannt Dohmann, Pablo | Technical University of Munich |
Hirche, Sandra | Technical University of Munich |
Keywords: Event-triggered and self-triggered control, Networked robotic systems, Consensus
Abstract: Consensus and synchronization are fundamental concepts for the coordination of cooperating multi-robot teams. Applications like cooperative manipulation may require not only synchronization of the position, but also of the orientation of the individual agents. The pose of the agent can be described within the special Euclidean group and common results for coordination have to be adapted. We propose a control framework for full-pose synchronization in SE(3) for a team of Euler-Lagrange agents, relying only on relative information in the absence of a global coordinate frame. The framework consists of an inner loop for feedback linearization and an outer loop for pose synchronization. The measurements are taken by external sensors and communicated to the respective agents via a common communication network. To deal with limited communication bandwidth, we propose an event-triggered update strategy for the relative measurements. Finally, the efficacy of the proposed control and triggering law is illustrated in simulations.
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14:50-15:10, Paper WeB10.5 | |
Event-Triggered Consensus for Continuous-Time Distributed Estimation |
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Perez-Salesa, Irene | University of Zaragoza |
Aldana-López, Rodrigo | Universidad De Zaragoza |
Sagues, Carlos | Universidad De Zaragoza |
Keywords: Sensor networks, Consensus, Distributed control and estimation
Abstract: Distributed sensor networks have gained interest thanks to the developments in processing power and communications. Event-triggering mechanisms can be useful in reducing communication between the nodes of the network, while still ensuring an adequate behaviour of the system. However, very little attention has been given to continuous-time systems in this context. In this work, we propose a strategy for distributed state estimation in sensor networks, based on average dynamic consensus of the continuous measurements. While communication between nodes is discrete and heavily reduced due to the event-triggering mechanism, our method ensures that the nodes are still able to produce a continuous estimate of the global average measurement and the state of the plant, within some tuneable error bounds.
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15:10-15:30, Paper WeB10.6 | |
A Data-Driven Survival Modelling Approach for Predictive Maintenance of Battery Electric Trucks |
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Luo Wang, Hao | Einride |
Ma, Xiaoliang | KTH Royal Institute of Technology |
Arnäs, Per Olof | Einride |
Keywords: Fault detection and diagnosis, Nonparametric methods, Intelligent Transportation Systems
Abstract: Predictive Maintenance (PdM) aims to estimate the optimal moment when the maintenance of an industrial asset should be performed according to its actual health status. The goal is to minimise the costs, by finding the optimal point where the sum of the prevention cost and the repair cost is at the lowest. Data-driven solutions can help build more cost-efficient maintenance strategies by providing a tool to predict whether the asset is close to suffering a real breakdown. This paper focuses on Survival-Analysis-based Predictive Maintenance applied to the case of Battery Electric Trucks (BET). Cox Proportional Hazards and Random Survival Forests are adopted for modelling the time-to-failure and the associated survival functions. Historical telematics data from electric heavy-duty vehicles in operations are used to train the models. Feature selection and hyperparameter tuning techniques are implemented to improve the model performance.
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WeB11 |
Room 411 |
Space Exploration and Control |
Regular Session |
Chair: Kumar, Shashi Ranjan | Indian Institute of Technology Bombay |
Co-Chair: Castaldi, Paolo | University of Bologna |
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13:30-13:50, Paper WeB11.1 | |
Constrained Reaction Wheel Desaturation and Attitude Control of Spacecraft with Four Reaction Wheels |
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Castroviejo Fernandez, Miguel | University of Michigan |
Kolmanovsky, Ilya V. | University of Michigan |
Keywords: Control of systems in vehicles, Guidance, navigation and control of vehicles
Abstract: The paper addresses a problem of constrained spacecraft attitude stabilization with simultaneous reaction wheel (RW) desaturation. The spacecraft has a reaction wheel array (RWA) consisting of four RWs in a pyramidal configuration. The developments exploit a spacecraft dynamics model with gravity gradient torques. The linearized dynamics are shown to be controllable at almost all RWA configurations. Configurations that result in the highest Degree of Controllability are elucidated. A strategy that combines an incremental reference governor and time-distributed model predictive control is proposed to perform constrained RW desaturation at low computational cost. Simulation results of successful RW desaturation maneuvers subject to spacecraft pointing constraints, RW zero-speed crossing avoidance and limits on control moments are reported.
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13:50-14:10, Paper WeB11.2 | |
Momentum-Based Learning of Nash Equilibria for LISA Pointing Acquisition |
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Gomez, Aitor | Aalborg University |
Al Ahdab, Mohamad | Aalborg University |
Keywords: Space exploration and transportation, High accuracy pointing, Extremum seeking and model free adaptive control
Abstract: This paper addresses the pointing acquisition phase of the Laser Interferometer Space Antenna (LISA) mission as a guidance problem. It is formulated in a cooperative game setup, which solution is a sequence of corrections that can be used as a tracking reference to align all the spacecraft' laser beams simultaneously within the tolerances required for gravitational wave detection. We propose a model-free learning algorithm based on residual-feedback and momentum, for accelerated convergence to stable solutions, i.e. Nash Equilibria. Each spacecraft has 4 degrees of freedom, and the only measured output considered are laser misalignments with the local interferometer sensors. Simulation results demonstrate that the proposed strategy manages to achieve absolute misalignment errors <1 microrad in a timely manner.
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14:10-14:30, Paper WeB11.3 | |
Fuel-Optimal Powered Descent Guidance for Hazardous Terrain |
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Sheikh, Zeeshan Basar | Indian Institute of Technology, Madras |
Ghosh, Satadal | Indian Institute of Technology Madras |
Keywords: Space exploration and transportation, Guidance, navigation and control of vehicles, Autonomous systems
Abstract: Future interplanetary missions will carry more and more sensitive equipment critical for setting up bases for crewed missions. The ability to manoeuvre around hazardous terrain thus becomes a critical mission aspect. However, large diverts and manoeuvres consume a significant amount of fuel, leading to less fuel remaining for emergencies or return missions. Thus, requiring more fuel to be carried onboard. This work presents fuel-optimal guidance to avoid hazardous terrain and safely land at the desired location. We approximate the hazardous terrain as step-shaped polygons and define barriers around the terrain. Using an augmented cost functional, fuel-optimal guidance command, which avoids the terrain, is derived. The results are validated using computer simulations and tested against many initial conditions to prove their effectiveness.
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14:30-14:50, Paper WeB11.4 | |
Single-State Weighted Particle Filter with Application to Earth Observation Missions |
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Donati, Cesare | Politecnico Di Torino |
Mammarella, Martina | CNR |
Dabbene, Fabrizio | CNR |
Keywords: Decision making and autonomy, sensor data fusion, Guidance, navigation and control of vehicles, High accuracy pointing
Abstract: To push the boundaries of autonomy in space, the spacecraft must rely on its own sensors to achieve positioning and environmental perception. In this context, the key problem of autonomous navigation is the nonlinear state estimation of the spacecraft in a dynamic 3D environment. In this paper, we propose a new approach based on a single-state sub-partitioning of the state vector and a partial updating of the vector of weights according to the specific information provided by each sensor. In this way, we avoid to lose information in the resampling phase thanks to a parallelization approach. The proposed method has been applied to an Earth observation mission and the efficacy of the proposed approach is demonstrated with a numerical example using a high-fidelity orbital simulator.
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14:50-15:10, Paper WeB11.5 | |
Resilient Composite Learning Neuro-Adaptive Integrated Guidance and Control for Reusable Launch Vehicle |
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Castaldi, Paolo | University of Bologna |
Emami, Seyyed Ali | Sharif University of Technology |
Mallipeddi, Siva Kumar | University of Bologna |
Simani, Silvio | University of Ferrara |
Keywords: Space exploration and transportation, Guidance, navigation and control of vehicles, Neural networks
Abstract: An integrated guidance and control system for tracking a reference flight path trajectory of a reusable launch vehicle in the presence of model uncertainties, external disturbances, and measurement noises is proposed. To achieve this goal, a properly-trained feedforward neural network to estimate the uncertainties in conjunction with a disturbance observer, which estimates external disturbances and the estimation error made by the neural network, is implemented in the scheme. In addition, a state observer is designed whose state estimation error is included (along with the tracking error) in the learning algorithm (of both the neural network and the disturbance observer); such learning is called composite learning. The combined neural network and state observer (employed in both the guidance and control loops) can consistently compensate for different complex and/or uncertain terms in the dynamic model of a reusable launch vehicle. More specifically, the introduced design results in an asymptotic tracking of the reference command, thereby providing a resilient flight control system. Extensive simulations are performed to show the effectiveness and robustness of the proposed integrated guidance and control system for trajectory tracking in the presence of uncertainties, aerodynamic disturbances, and measurement noises.
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15:10-15:30, Paper WeB11.6 | |
Free Will Arbitrary Time Consensus-Based Distributed Spacecraft Formation Control |
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Pal, Rajib Shekhar | Indian Institute of Technology Bombay |
Kumar, Shashi Ranjan | Indian Institute of Technology Bombay |
Mukherjee, Dwaipayan | Indian Institute of Technology Bombay |
Keywords: Autonomous systems, Multi-agent systems
Abstract: A distributed formation control scheme is proposed for achieving a desired formation of multiple spacecraft in orbit around the Earth within a free will arbitrary settling time, over an undirected communication network. Using the Clohessy-Wiltshire equations as relative position dynamics model for the spacecraft in a circular reference orbit around the Earth, the proposed control strategy is able to achieve the desired formation of the spacecraft using only relative position measurements. Simulations are presented to demonstrate the effectiveness of the proposed strategy.
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WeB12 |
Room 412 |
Identification and Control for Mechatronics |
Regular Session |
Chair: Csencsics, Ernst | Vienna University of Technology |
Co-Chair: Dixon, Roger | University of Birmingham |
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13:30-13:50, Paper WeB12.1 | |
Controlling the Amplitude of a Resonant Rotational Reluctance Actuated Scanning Mirror System |
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Pechgraber, Daniel | TU Wien |
Csencsics, Ernst | Vienna University of Technology |
Yoo, Han Woong | TU Wien |
Schitter, Georg | Vienna University of Technology |
Keywords: Mechatronics, Identification and control methods, Mechatronic systems
Abstract: This paper describes the development and implementation of three driving strategies for the oscillation amplitude control of a resonant rotational reluctance actuated scanning mirror system. The three driving strategies exploit control of current input amplitude, pulse duration, and the phase between the input and the mover angle. Linear PI-controllers are developed for each driving strategy for the linearized plant around an operating point of the highly nonlinear system. The implemented driving strategies are compared over a wide operating range of the scanning mirror system, regarding their closed-loop dynamics in the time-domain, revealing their fundamental dierences. Phase-control is the most promising control strategy, delivering the highest closed-loop bandwidth of at least 11 Hz over the entire investigated operating range at worst with a rise-time of 30 ms at a step response.
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13:50-14:10, Paper WeB12.2 | |
Modeling and Control of Electromagnetic Coil System Using Model Order Reduction-Based LSSVM Method |
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Fang, Shan | University of Science and Technology of China |
Sun, Zhiyong | Hefei CAS |
Cheng, Yu | Michigan State University |
Cheng, Erkang | Institute of Intelligent Machines, HFIPS, Chinese Academy of Sci |
Chen, Liangliang | Michigan State University |
Song, Bo | Department of Electrical and Computer Engineering, MichiganState |
Keywords: Identification and control methods, Micro and nano mechatronic Systems, Nonlinear system identification
Abstract: Magnetic microrobot (MM) is promising for in-body therapy due to its advantage of untethered controllability. Since the motion of MMs can be directly manipulated by the magnetic field (MF) created by electromagnetic coil systems, it is essential to study the MF generation control methods. In this study, iron core-based solenoids are employed in an electromagnetic coil system that can produce a stronger MF than regular coil systems. However, the coil system presents hysteretic nonlinearity due to the iron core's coercivity, which degrades closed-loop control performances. To tackle this challenge, an effective hysteresis compensation method is developed to linearize the solenoid system. Specifically, the least squares support vector machine (LSSVM) is adopted to model the hysteretic behavior of the solenoid system, and the discrete empirical interpolation method (DEIM) is applied to reduce complexity of the model for enhancing calculation efficiency. Based on the LSSVM and DEIM approaches, a highly efficient LSSVM-DEIM hysteresis compensator is developed. In order to generate precise dynamic MF effectively, the LSSVM-DEIM hysteresis compensator is combined with prevalent feedback controllers to form composite control schemes. Experiments show that the control system with the LSSVM-DEIM hysteresis compensator can produce a more accurate MF compared with that of the benchmark control methods.
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14:10-14:30, Paper WeB12.3 | |
A Singular Perturbation Approach for the Control of Electromagnetic Actuators |
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Ariba, Yassine | INSA |
Gouaisbaut, Frederic | LAAS CNRS |
Keywords: Identification and control methods, Application of nonlinear analysis and design, Motion control systems
Abstract: The paper is devoted to the control of electromagnetic actuators. Compared to most results in the literature, the design explicitly takes into account the nonlinearities and the magnetic saturation. An approach based on singularly perturbed systems is proposed to take advantage of the different time scales of the model and provide a minimal complexity control law. Associated with an integral action, this control law ensures accuracy and robustness w.r.t. some disturbances and some unknown parameters of the actuator. The use of the singular perturbation method allows also to limit the implementation complexity compared to classical methods such as backstepping control. The synthesis of the control law is then tested through simulations that illustrate the efficiency of the method.
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14:30-14:50, Paper WeB12.4 | |
A Kernel-Based Identification Approach to LPV Feedforward: With Application to Motion Systems |
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van Haren, Max | Eindhoven University of Technology |
Blanken, Lennart | Eindhoven University of Technology |
Oomen, Tom | Eindhoven University of Technology |
Keywords: Mechatronics, Identification and control methods, Motion control systems
Abstract: The increasing demands for motion control result in a situation where Linear Parameter-Varying (LPV) dynamics have to be taken into account. Inverse-model feedforward control for LPV motion systems is challenging, since the inverse of an LPV system is often dynamically dependent on the scheduling sequence. The aim of this paper is to develop an identification approach that directly identifies dynamically scheduled feedforward controllers for LPV motion systems from data. In this paper, the feedforward controller is parameterized in basis functions, similar to, e.g., mass-acceleration feedforward, and is identified by a kernel-based approach such that the parameter dependency for LPV motion systems is addressed. The resulting feedforward includes dynamic dependence and is learned accurately. The developed framework is validated on an example.
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14:50-15:10, Paper WeB12.5 | |
Disturbance Observer-Based Sliding Mode Controller for Regulating Pantograph–Catenary Contact Force |
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Huayu, Duan | University of Birmingham |
Dixon, Roger | University of Birmingham |
Stewart, Edd | The University of Birmingham |
Li, Linxiao | University of Birmingham |
Olaby, Osama | University of Birmingham |
Keywords: Identification and control methods, Mechatronics for mobility systems, Modeling
Abstract: For most electrified railways, pantographs play a vital role in transmitting energy from overhead line to vehicles, and therefore a stable and continuous contact behavior is required. This paper proposes a disturbance observer-based sliding mode controller (DO-SMC) for the problem of pantograph–catenary contact force regulation. The simulation results show that the DO-SMC with a chattering alleviation approach can effectively reduce contact force fluctuation through a reasonable control input.
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15:10-15:30, Paper WeB12.6 | |
Position-And-Torque-Sensorless Admittance Control with State Estimation Considering Dq-Axis Cross-Coupling Factors |
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Shimamoto, Keita | YASKAWA Electric Corporation |
Murakami, Toshiyuki | Keio Univ |
Keywords: Identification and control methods, Motion control systems, Mechatronics
Abstract: This paper presents a position estimation compensation method considering dq-axis cross-coupling factors of Interior Permanent Magnet Synchronous Motors (IPMSMs) inductance for position-and-torque-sensorless admittance control. The cross-coupling factors are from dq-axis mutual inductance and deteriorate control and position estimation performance in control methods without the model. Since dq-axis cross-coupling factors of inductance vary with the rotor position and the current, measurement and estimation of the values are difficult. The proposed method estimates the cross-coupling factors and position estimation errors using dq-axis current variation from the injected voltage. In addition, the proposed method compensates the estimated position based on a voltage equation, including the dq-axis cross-coupling factors, by adding the estimated error. As a result, the vibration of current, velocity, and estimated reaction torque were reduced, and the performance of a position-and-torque-sensorless admittance control system was improved. The experimental results show the proposed method's validity and response by the sensorless admittance control.
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WeB14 |
Room 414 |
On Software Tools and Applications of Discrete Event Systems |
Invited Session |
Chair: Cai, Kai | Osaka Metropolitan University |
Co-Chair: Reniers, Michel | TU/e |
Organizer: Meira-Goes, Romulo | Pennsylvania State University |
Organizer: Reniers, Michel | TU/e |
Organizer: Cai, Kai | Osaka Metropolitan University |
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13:30-13:50, Paper WeB14.1 | |
UltraDES Project - a Multiplatform Discrete Event Systems Tool (I) |
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Alves, Lucas Vinícius Ribeiro | Universidade Federal De Minas Gerais |
Pena, Patricia Nascimento | Universidade Federal De Minas Gerais |
Keywords: Discrete event modeling and simulation, Supervisory control and automata, Petri nets
Abstract: In this paper we present the UltraDES Project, composed of the UltraDES library, as well as a wrapper to Python and a Web Application. UltraDES is an open source project, available at Github. It has several functions and data structures for analysis and control of Discrete Event Systems and is under development since 2013. Currently, a new set of algorithms were implemented in the context of Supervisory Control Theory, but also some basic functions for Petri nets.
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13:50-14:10, Paper WeB14.2 | |
CIF: Towards an Industrial Strength Synthesis-Based Supervisory Control Engineering Toolset (I) |
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Reniers, Michel | TU/e |
Hendriks, Dennis | Eindhoven University of Technology |
Keywords: Discrete event modeling and simulation, Supervisory control and automata, Reachability analysis, verification and abstraction of hybrid systems
Abstract: In this discussion paper, we highlight a synthesis-based engineering (SBE) framework for the engineering of supervisory controllers. The engineering of supervisory controllers for large and complex cyber-physical systems requires dedicated engineering support. The Compositional Interchange Format (CIF) language and toolset have been developed for this purpose. CIF is part of the Eclipse Supervisory Control Engineering Toolkit (ESCET) project. In this paper we discuss language and tool aspects that are necessary for industrial application, but under-exposed in academic research efforts.
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14:10-14:30, Paper WeB14.3 | |
Software Tool for Distribution of Linear Temporal Logic Specifications (I) |
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Hustiu, Ioana | Technical University of Iasi |
Mahulea, Cristian | University of Zaragoza |
Kloetzer, Marius | Technical University of Iasi |
Keywords: Discrete event modeling and simulation
Abstract: This work presents the implementation of a software tool that ensures the execution of a global Linear Temporal Logic (LTL) specification for a team of mobile agents that are evolving in a static and known environment cluttered with regions of interest. The software is build on formalisms that extend our previous work, with the main contribution of handling strictly more expressive missions that also allow negations (or temporal avoidance) of some regions of interest. An algorithm is provided for decomposing the global LTL mission into independent robots’ tasks, together with a flow diagram of the entire method that solves the path planning problem. Simulations and comparative results are discussed for a case study, in order to support the usefulness of the software tool.
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14:30-14:50, Paper WeB14.4 | |
MDESops: An Open-Source Software Tool for Discrete Event Systems Modeled by Automata (I) |
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Meira-Goes, Romulo | Pennsylvania State University |
Wintenberg, Andrew | The University of Michigan, Ann Arbor |
Matsui, Shoma | Queen's University |
Lafortune, Stephane | Univ. of Michigan |
Keywords: Supervisory control and automata, Diagnosis of discrete event and hybrid systems, Discrete event modeling and simulation
Abstract: The salient features of the new software tool MDESops are presented. MDESops is Python-based and open-source. Its focus is the analysis and control of discrete event systems (DES) modeled by finite-state automata. MDESops has core functions to manipulate deterministic and nondeterministic automata, including parallel composition and determinization. It has functions to analyze diagnosability and opacity properties. MDESops also includes functions that implement both standard and more recent algorithmic procedures from the theory of supervisory control of DES, including synthesis of supervisors for partially-observed systems, synthesis of attackers in systems with compromised sensors, and synthesis of supervisors resilient to deception attacks. It is the hope that MDESops can serve as a useful platform for algorithm development and prototyping in DES research.
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14:50-15:10, Paper WeB14.5 | |
Lupremica – Lua Scripting for Supremica (I) |
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Fabian, Martin | Chalmers University of Technology |
Malik, Robi | The University of Waikato |
Mohajerani, Sahar | Chalmers University of Technology |
Keywords: Supervisory control and automata, Discrete event modeling and simulation
Abstract: Supremica is a software tool that implements several state-of-the-art algorithms to manipulate discrete-event systems, such as different types of compositions and compositional supervisor synthesis. Lua is a light-weight programming language suitable as a scripting language embedded into other applications. This paper describes the use of Lua as a scripting language for Supremica. To this end, the LuaJ interpreter is added to Supremica as a bridge between the Java-based implementation of Supremica and the Lua scripts. In this way, Supremica’s entire Java API is made available to Lua scripts. Thus, scripts can automatically create automata, and manipulate them with all the algorithms available in Supremica and further manipulate the result with new algorithms implemented by Lua scripts. This opens up a new world of possibilities to try out new ideas and to extend the power of Supremica.
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15:10-15:30, Paper WeB14.6 | |
Improved Representations of Gantt Charts in Manufacturing (I) |
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Holmes, Nikolaus | Eindhoven University of Technology |
Reniers, Michel | TU/e |
van der Sanden, Bram | Eindhoven University of Technology |
Keywords: Discrete event modeling and simulation, Event-based control, Supervisory control and automata
Abstract: Gantt charts are a form of bar chart consisting of multiple rows each representing different tasks while the horizontal length of a bar in a row represents the start and end times of a specific task. Gantt charts are widely applicable in all manner of fields, and are commonly used to aid in the illustration of schedules as they are able to clearly show the time frame of tasks in a schedule as well as illustrate connections/dependencies between tasks. Within manufacturing, Gantt charts are widely used to visualize production systems as they can easily illustrate the dependencies between different machines/processes in a system while also providing time information. This allows for systems to be more easily analyzed and makes complex systems more intuitive to understand. While Gantt charts are widely used in manufacturing, the functionality of the academic tools by which these charts can be manipulated is often not very deep, with processes such as generating different representations of the same chart having to be done manually; a task which makes these tools rather cumbersome to use for complex systems such as those found in real-life manufacturing scenarios. This paper will discuss the necessity of improving the Gantt chart representations of manufacturing systems to better display the connections between components, as well as the method of automating this process and why said automation is crucial for even moderately complex systems. It will also be discussed how this automation process could be modified to allow for different types of sorting methods.
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WeB15 |
Room 415 |
Emerging Challenges and Directions of Advanced Battery Management I |
Open Invited Session |
Chair: Trimboli, Scott | University of Colorado |
Co-Chair: Plett, Gregory L. | Univ of Colorado at Colorado Springs |
Organizer: Plett, Gregory L. | Univ of Colorado at Colorado Springs |
Organizer: Trimboli, Scott | University of Colorado |
Organizer: Onori, Simona | Stanford University |
Organizer: Fang, Huazhen | University of Kansas |
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13:30-13:50, Paper WeB15.1 | |
A Model-Based Battery Dataset Recovery Method Base on Actual Vehicle Considering Aging (I) |
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Zhu, Jingzhe | Shanghai Jiao Tong University |
Ziying, Huang | Shanghai Jiao Tong University |
Li, Jiaqi | Shanghai Jiao Tong University |
Gao, Yizhao | Carnegie Mellon University |
Zhang, Xi | Shanghai Jiaotong University |
Fan, Guodong | Shanghai Jiao Tong University |
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Automotive system identification and modelling, Information displays/system
Abstract: High-quality historical data of battery is important for state estimation and management. However, limited by bandwidth of 4G network and storage capacity, the cloud only receives low-frequency (LF) data and a few high-frequency (HF) signals. This paper proposes a model-based method to transfer adequate battery data between vehicle and cloud at a low cost. Firstly, a training dataset is built from real-world vehicle data. Then, a multi-task learning (MTL) model under semi-supervised learning (SSL) framework is proposed to learn HF voltage representation of each battery cell. SSL framework uses a large number of unlabeled low-frequency voltages to improve the voltage frequency recovery accuracy. MTL framework enables the model to focus on battery aging and solve the problem of target domain drifting over time. Finally, both real-world vehicle and experimental data are used to compare the results of different methods on the voltage recovering task. The results show that the proposed method can reduce the average voltage recovery error to less than 7mV at various driving conditions.
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13:50-14:10, Paper WeB15.2 | |
Time-Domain System Identification of Li-Ion Batteries from Non-Zero Initial Conditions (I) |
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Adel, Abderrahmane | University of Bordeaux |
Malti, Rachid | University of Bordeaux |
Briat, Olivier | University of Bordeaux |
Keywords: Automotive system identification and modelling
Abstract: Electrochemical Impedance Spectroscopy (EIS) allows characterizing electrochemical behavior of Lithium-ion batteries. However, it requires the battery to be at a relaxed state which is quite time-consuming during data acquisition process at different State-Of-Charge (SOC) levels. A time relaxation is usually observed of about 1h at each SOC level. In the prospect to reduce the measurement time, this paper presents a time-domain identification method using non-zero initial conditions of a fractional-order equivalent circuit model (FO-ECM). A two-stage iterative algorithm is developed. It estimates at one stage the system free response, due to the past initialization, and the system forced response due to the input/output signal. It uses, at the second stage, an output error model to estimate model parameters. The algorithm is iterated until convergence. The proposed identification algorithm is applied to identify a Li-ion battery FO-ECM using experimental data.
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14:10-14:30, Paper WeB15.3 | |
Bayesian Hierarchical Modelling for Battery Lifetime Early Prediction (I) |
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Zihao, Zhou | University of Oxford |
Howey, David | University of Oxford |
Keywords: Automotive system identification and modelling, Modeling, supervision, control and diagnosis of automotive systems
Abstract: Accurate prediction of battery health is essential for real-world system management and lab-based experiment design. However, building a life-prediction model from different cycling conditions is still a challenge. Large lifetime variability results from both cycling conditions and initial manufacturing variability, and this---along with the limited experimental resources usually available for each cycling condition---makes data-driven lifetime prediction challenging. Here, a hierarchical Bayesian linear model is proposed for battery life prediction, combining both individual cell features (reflecting manufacturing variability) with population-wide features (reflecting the impact of cycling conditions on the population average). The individual features were collected from the first 100 cycles of data, which is around 5-10% of lifetime. The model is able to predict end of life with a root mean square error of 3.2 days and mean absolute percentage error of 8.6%, measured through 5-fold cross-validation, overperforming the baseline (non-hierarchical) model by around 12-13%.
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14:30-14:50, Paper WeB15.4 | |
Real-Time Battery State of Charge and Parameters Estimation through Multi-Rate Moving Horizon Estimator (I) |
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Desai, T.K. | TU Delft |
Oliva, Federico | Tor Vergata University of Rome |
Ferrari, Riccardo M.G. | Delft University of Technology |
Carnevale, Daniele | Università Di Roma, Tor Vergata |
Keywords: Automotive system identification and modelling, Health monitoring and diagnosis
Abstract: For reliable and safe battery operations, accurate and robust State of Charge (SOC) and model parameters estimation is vital. However, the nonlinear dependency of the model parameters on battery states makes the problem challenging. We propose a Moving-Horizon Estimation (MHE)-based robust approach for joint state and parameters estimation. Dut to all the time scales involved in the model dynamics, a multi-rate MHE is designed to improve the estimation performance. Moreover, a parallelized structure for the observer is exploited to reduce the computational burden, combining both multi-rate and a reduced-order MHEs. Results show that the battery SOC and parameters can be effectively estimated. The proposed MHE observers are verified on a Simulink-based battery equivalent circuit model.
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14:50-15:10, Paper WeB15.5 | |
A Contrastive Learning Battery State of Health Estimation Method Based on Self-Supervised Aging Representation (I) |
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Li, Jiaqi | Shanghai Jiao Tong University |
Zhu, Jingzhe | Shanghai Jiao Tong University |
Ziying, Huang | Shanghai Jiao Tong University |
Fan, Guodong | Shanghai Jiao Tong University |
Zhang, Xi | Shanghai Jiaotong University |
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Automotive system identification and modelling, Electric and solar vehicles
Abstract: Accurate state of health (SOH) estimation is crucial to improve the performance and reduce the maintenance cost of electric vehicles. Existing data-driven SOH estimation methods mainly focus on using sufficient capacity labels to train deep learning models, which tend to establish the mapping between health indicators and residual capacity. However, the number of available supervised labels in the actual driving data is usually limited, resulting in substantial deterioration of model performance. To address this label-insufficient issue, this article proposes a novel self-supervised SOH estimation method based on contrastive learning. First, a two-stage relation network composed of a feature encoder and a relation module is proposed to model the similarity between different battery samples in a contrastive learning paradigm. Meanwhile, a representation space is obtained where embeddings from different samples aggregate with battery aging. Then, the difference of cycle number in a single battery sample is taken as the self-supervised aging pseudo label. Rather than establishing the conventional mapping between SOH and its indicators, the proposed framework directly learns the similarity between batteries in different aging states, and thus manages to eliminate the dependence on large number of supervised labels. Finally, experimental results show that compared with end-to-end mapping, the root mean square error of the proposed method is reduced by 33% and 36% on average under insufficient and sufficient label conditions, respectively.
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15:10-15:30, Paper WeB15.6 | |
Improved Parameter Estimation of the Doyle-Fuller-Newman Model by Incorporating Temperature Dependence (I) |
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le Roux, Francis Anne | Eindhoven University of Technology |
Bergveld, Henk Jan | Eindhoven University of Technology |
Donkers, M.C.F. (Tijs) | Eindhoven University of Technology |
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Electric and solar vehicles, Automotive system identification and modelling
Abstract: Abstract: Identifiability remains a key issue in estimating the model parameters of the Doyle-Fuller-Newman (DFN) model, which implements physics-based modeling of lithium-ion cells. This paper proposes the inclusion of physics-based temperature relations within the DFN model and the parameter estimation technique, in which model parameters are estimated over a wide temperature range. We evaluate the effect of including physics-based relations on the identifiability of the model, as well as its voltage prediction accuracy. The implementation of physics-based relations results in parameters that are physically meaningful, and comparable model accuracies to the original parameter estimation technique, in which the model parameters are identified at individual temperatures and physics-based temperature relations are not included. We further evaluate the robustness of the parameter estimation technique by perturbing initial conditions and compare its affect on the presened and the original parameter estimation technique. We find the presented parameter estimation technique to be more robust and reliable. Finally, we compare the DFN model to an equivalent-circuit model and find the DFN model to be comparable in accuracy whilst having a better representation of the internal states of the cell.
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WeB16 |
Room 416 |
Process Control I |
Regular Session |
Chair: Engell, Sebastian | TU Dortmund |
Co-Chair: Ricardez-Sandoval, Luis | University of Waterloo |
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13:30-13:50, Paper WeB16.1 | |
Multivariable Modeling and Feedback Control of Reactive Sputtering |
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Wölfel, Christian Tobias | Ruhr-Universität Bochum |
Keywords: Process control applications, Applications in advanced materials manufacturing
Abstract: A control design method to stabilize multivariable reactive sputter processes is developed. A new model is presented to describe the nonlinear deposition process with respect to the set argon gas flow, the set reactive gas flow and the generator power as the inputs. Outputs are the total pressure, the reactive gas pressure and the self-bias voltage. The control-oriented model is analyzed with regard to its static behavior and its stability properties. Based on this analysis, a novel design method for the process control is discussed. Experimental data illustrate the applicability of the developed control system to accomplish set-point following for the control loop despite the presence of uncertainties in the process parameters.
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13:50-14:10, Paper WeB16.2 | |
Wafer Temperature Control on an Electrostatic Chuck with Helium Pressure |
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Hayashi, Daisuke | HORIBA STEC, Co., Ltd |
Takijiri, Kotaro | HORIBA STEC, Co., Ltd |
Ueda, Takayuki | HORIBA STEC, Co., Ltd |
Keywords: Industrial applications of process control, Model predictive and optimization-based control, Process control applications
Abstract: We controlled wafer temperatures by leveraging the helium (He) pressures provided into a two-zone electrostatic chuck (ESC) in a semiconductor process chamber. A wafer was clamped onto the ESC and a heat transfer model was constructed to make the equation of state for the control. As the equation was nonlinear, model predictive control (MPC) was employed to determine the optimal settings of He pressure in every sampling step. After checking the validity of the model and the simulation, we experimentally demonstrated the temperature control using the test chamber. The MPC algorithm worked well to adjust the He pressure, which resulted in each wafer process zone achieving the target temperature value. This method can be useful to regulate wafer temperatures against drifts present in the process.
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14:10-14:30, Paper WeB16.3 | |
Experimental Application of Real-Time Optimization with Modifier Adaptation and Quadratic Approximation to a Reactive Extrusion Process |
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Cegla, Maximilian | TU Dortmund |
Buczko, Aleksandra | Fraunhofer ICT |
Kemmerling, Simon | Fraunhofer ICT |
Engell, Sebastian | TU Dortmund |
Keywords: Process control applications, Real time optimization and control, Industrial applications of process control
Abstract: In this contribution, Real-Time Optimization with Modifier Adaptation and Quadratic Approximation (MAWQA) is experimentally applied to a pilot-scale 18 mm reactive extruder for the production of hydrophobically modified ethoxylated urethanes which are used as rheological paint additives. Standard model-based control is in this application not applicable because of the complex coupling of the chemical reaction, complex internal flows within the equipment, and a high sensitivity to external disturbances. The optimization is performed with the goal to minimize the specific energy requirement for the product by changing the overall throughput and the barrel temperature locally while meeting a hard constraint on the product quality. The product quality is determined by the viscosity of the product which is measured online with a capillary viscometer. In contrast to other work, the MAWQA method is applied here purely data-based without using a physical model. Despite the absence of a rigorous model, the method converged to the optimum after 6 initial probing moves and 4 iterations where the product quality constraints were already met.
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14:30-14:50, Paper WeB16.4 | |
Economic Model Predictive Control of a Recirculating Aquaculture System |
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Patron, Gabriel David | University of Waterloo |
Ricardez-Sandoval, Luis | University of Waterloo |
Keywords: Batch and semi-batch process control, Modeling and control of agriculture, Estimation and control in biological systems
Abstract: The recirculating aquaculture systems (RAS) has been proposed to reduce the water consumption of commercial aquaculture. RAS removes organic and particulate waste from fish tank water while also aerating; as such, the treated water can be recycled back into the tanks. In this work, we treat the RAS as a batch process such that economic model predictive control (EMPC) can be applied using a mechanistic process model. The EMPC, which considers fish production profits as well as material utility and electricity costs for RAS, is deployed for various water temperatures such that its effect on the fish growth and economics are quantified. Moreover, batch length is also determined through tracking of the process profit trajectory. The results show that the EMPC-operated RAS can substantially increase the fish sales price with time-varying control decisions. Moreover, the EMPC is shown to adjust its operating policy mid-batch to accommodate for temperature disturbances.
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14:50-15:10, Paper WeB16.5 | |
Shape–Constrained Moving Horizon Estimators for Reaction Systems |
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Tiwari, Avinash | Indian Institute of Technology Madras |
Bhatt, Nirav | Indian Institute of Technology Madras |
Keywords: Batch and semi-batch process control, Parameter and state estimation, Estimation and filtering
Abstract: In reaction systems, state estimators are used to improve the quality of estimates using measurements and process models with the number of moles or concentrations as states. The model of reaction systems can be reformulated in the extent domain with the reaction and flow extents as states. This work exploits the properties of the extents, such as nonnegativity and monotonicity, and formulates nonlinear and linear Shape-Constrained Moving Horizon Estimators (SCMHE) for reaction systems. It is shown that the linear SCMHE is a quadratic programming problem, and hence, it is computationally less expensive. The performance of the SCMHE schemes is compared with the Extended Kalman filters (EKF) and MHE in the concentration domain via simulation studies using two examples, namely, gas-phase isothermal batch reactor and lactic acid production in a fed-batch reactor. It is shown that the linear SCMHE provides better performance than EKF with a similar average computational time, while nonlinear SCMHE is computationally cheaper and performs better than the MHE in the concentration or mole domain.
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15:10-15:30, Paper WeB16.6 | |
Frequent Event Pattern Extraction of Drilling Time Series Using Change Point Detection and Event Sequence Generation (I) |
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Li, Yupeng | China University of Geosciences |
Hu, Wenkai | China University of Geosciences |
Cao, Weihua | China University of Geosciences |
Gopaluni, Bhushan | University of British Columbia |
Cao, Liang | University of British Columbia |
Gan, Chao | China University of Geosciences |
Wu, Min | China University of Geosciences |
Keywords: Process monitoring and fault diagnosis, Statistical methods/signal analysis for FDI
Abstract: In drilling processes, non-stationary phases corresponding to shifts between operating conditions and changes in downhole formations typically lead to false alarms. Extracting these frequent event patterns is critical to build drilling process monitoring and fault diagnosis models. This study aims to extract the frequent event patterns associated with non-stationary phases in drilling time series. In this way, diversified information related to signal changes under normal conditions can be obtained, which is beneficial for suppressing false alarms and improving fault detection performance. The main contributions of this study are twofold: 1) a non-stationary phase detection method is proposed to extract drilling frequent event patterns based on t-distributed stochastic neighbor embedding and relative unconstrained least-squares importance fitting; 2) an event sequence generation method is proposed to express drilling frequent event patterns with a group of symbols. The effectiveness of the proposed method is demonstrated by data from a real drilling project.
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WeB17 |
Room 417 |
Current Progress in Control and System Technology in Metal Processing
Industry |
Invited Session |
Chair: Kitada, Hiroshi | Nippon Steel Corporation |
Co-Chair: Tamaki, Hisashi | Kobe University |
Organizer: Kitada, Hiroshi | Nippon Steel Corporation |
Organizer: Yamaguchi, Osamu | JFE Steel Corporation |
Organizer: Iwatani, Toshiharu | KOBE STEEK, Ltd |
Organizer: Horikawa, Tokujiro | Toshiba Mitsubishi-Electric Industrial Systems Corporation |
Organizer: Tamaki, Hisashi | Kobe University |
Organizer: Noda, Yoshiyuki | University of Yamanashi |
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13:30-13:50, Paper WeB17.1 | |
Wide-Area Vibration Monitoring of Ironworks Conveyors Using Panoramic High-Speed Vision (I) |
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Ishii, Idaku | Hiroshima University |
Shimasaki, Kohei | Hiroshima University |
Keywords: Measurement and instrumentation, Equipment condition monitoring, Condition monitoring
Abstract: A novel noncontact vision sensing method is introduced for wide-area monitoring of the operation of conveyors in ironworks by using high-speed telephoto active vision that can panoramically capture zoomed-in images at hundreds of frames per second. The effectiveness of the method was demonstrated in multiple-viewpoint monitoring of ironworks conveyors with high magnification by detecting several-dozens-of-hertz vibration and rotation of multiple belts and rollers.
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13:50-14:10, Paper WeB17.2 | |
A Log-Likelihood-Based Evaluation Metric for the Reproducibility and Simplicity of Logistics Graphs (I) |
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Takakura, Yuriko | Nippon Steel Corporation |
Mori, Junichi | Nippon Steel Corp |
Kobayashi, Hirokazu | Nippon Steel Corporation |
Keywords: Machine learning and data analytics in process control, Digital twins for power and process systems, Data visualization
Abstract: Logistics are sometimes complex and usually entail the interrelation of different processes. It is beneficial to visualize actual process-flow logs to better understand the underlying processes. However, it is difficult to analyze logistics using graph visualization as the graphs are typically quite large and complex. In the field of process mining, several metrics have been proposed in previous studies to examine the quality of process models created using process mining algorithms. However, these metrics evaluate the efficacy of the graph in terms of reproducing the actual process-flow logs. Thus, there is often process-flow information loss in the resulting graph structure when nodes or edges are aggregated to simplify the graph. To address these limitations, in this paper, we propose a maximum log-likelihood-based metric for measuring the reproducibility of graphs and define the concept in terms of how much of the actual process-flow information the graph retains. To obtain the metrics, we developed a graph model that can generate process-flow logs according to its probability parameters. In addition, we also developed an evaluation metric, which is a weighted sum of both the log-likelihood and model dimensions. An empirical evaluation was conducted using the actual process-flow patterns of steel-making process data. The results revealed that the maximum log-likelihood-based metric effectively evaluated the process by which the graphs with node and edge aggregations reproduced the actual process-flow patterns.
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14:10-14:30, Paper WeB17.3 | |
Add-On Harmonic Disturbance Cancellation Control in Continuous Hot-Dip Galvanizing Lines (I) |
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Marko, Lukas | TU Wien/CDL for Intelligent Process Control for High-Quality Ste |
Kugi, Andreas | TU Wien |
Steinboeck, Andreas | TU Wien |
Keywords: Advanced process control
Abstract: In continuous hot-dip galvanizing of steel strips, unwanted vibrations of the processed strip can significantly degrade the coating uniformity and quality. Thus, an increasing number of hot-dip galvanizing lines are equipped with electromagnetic strip stabilization devices to enable active strip-shape and vibration control. Typically, commercial strip stabilizers achieve adequate broad-band vibration attenuation. However, their disturbance rejection capabilities are usually insufficient in case of persistently exciting harmonic disturbances. This work proposes a new multivariable harmonic disturbance cancellation control strategy which can be used as add-on to the position control loop of an existing strip stabilization device. The unknown amplitude, phase angle, and disturbance frequency are estimated during online operation. The systematic consideration of controller-output and estimator constraints in the design guarantees a reliable and safe operation in the challenging industrial environment. The devised control system works well even in the case of non-persistently exciting harmonic disturbances. The effectiveness of the proposed control scheme is demonstrated by short- and long-term measurement results from an industrial hot-dip galvanizing line.
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14:30-14:50, Paper WeB17.4 | |
Current Progress in Control and System Technology in Metal Processing Industry (I) |
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Gong, Peng Xu | Central South University |
Pan, Dong | Central South University |
Jiang, Zhaohui | Central South University |
Yang, Chunhua | Central South University |
Gui, Weihua | Central South University |
Keywords: Artificial intelligence in mining, minerals and metals, Process observation and parameter estimation, Machine learning methods and applications
Abstract: The online measurement of molten iron temperature in blast furnace ironmaking process is an urgent need in the ironmaking industry, but under the influence of factors such as overflowing slag and dust, the online measurement of molten iron temperature based on infrared temperature measurement faces the problem of low measurement accuracy. Aiming at the interference of overflowing slag and dust, this paper proposes a method for online measurement of molten iron temperature after skimmer based on infrared vision. Firstly, an industrial-grade infrared visual temperature measurement system is designed to obtain infrared images of molten iron for a long time and stably after skimmer. Secondly, ShuffleNet v2 is used to identify the slag and dust interference states of molten iron after skimmer, and then the molten iron temperature mapping model during slag overflowing and the molten iron temperature compensation model during dust disturbance are established. Finally, the online accurate molten iron temperature (MIT) after skimmer is obtained. The temperature measurement experiment on the blast furnace site shows that the method can accurately obtain the MIT after skimmer online.
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14:50-15:10, Paper WeB17.5 | |
Automation on Thermal Control of Blast Furnace (I) |
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Hashimoto, Yoshinari | JFE Steel Corporation |
Masuda, Ryosuke | JFE Steel Corporation |
Keywords: Digital twins for power and process systems, Intelligent decision support systems, Process optimisation
Abstract: To achieve the automation of blast furnace operation, an automatic control system for hot metal temperature (HMT) was developed. To cope with the slow and complex process dynamics of the blast furnace, we constructed a control algorithm that predicts eight-hour-ahead HMT using a two-dimensional (2D) transient model and calculates optimal target pulverized coal ratio (PCR) and pulverized coal flow rate by non-linear model predictive control (NMPC). An evaluation in a real plant showed that the developed control system suppressed the effects of disturbances, such as the changes in the coke ratio and blast volume, and successfully reduced the average control error of HMT by 4.6 °C compared to the conventional manual operation. The developed control system has contributed to the reduction of reducing agent rate (RAR) and CO2 emissions.
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15:10-15:30, Paper WeB17.6 | |
Advanced Monitoring and Control of Alumina Concentration in Aluminum Smelting Cells (I) |
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Shi, Jing | Emirates Global Aluminium |
Wong, Choon-Jie | University of New South Wales |
Bao, Jie | The University of New South Wales |
Skyllas-Kazacos, Maria | University of New South Wales |
Welch, Barry | University of New South Wales |
Jassim, Ali | Emirates Global Aluminium |
Mustafa, Mustafa | Emirates Global Aluminium |
Nikandrov, Konstantin | Emirates Global Aluminium |
Mahmoud, Mohamed | Emirates Global Aluminium |
Keywords: Industrial applications of process control, Advanced process control, Process control applications
Abstract: In an aluminum smelting cell, the alumina concentration plays a critical role in determining process stability and performance, thus it is always desirable to control the alumina concentration at a stable level within a reasonable range. However, the traditional logic-based alumina feed control strategies typically implement overfeed–basefeed–underfeed cycles to control the alumina concentration in a range, which causes significant variations in alumina concentration within the aluminum smelting cell, and risk transgression to perfluorocarbons (PFC) co-evolution. Different from the traditional methods, this paper presents an advanced cell monitoring and control approach which integrates a state estimator, model-based control and logic control to improve cell performances through tighter control of alumina concentration.
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WeB18 |
Room 418 |
Dynamics and Control of Biosystems and Bioprocesses |
Regular Session |
Chair: Shen, Xun | Osaka University |
Co-Chair: Gil, Juan Diego | University of Almeria |
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13:30-13:50, Paper WeB18.1 | |
Data-Driven Re-Stabilization of Gene Regulatory Network towards Early Medical Treatment |
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Shen, Xun | Osaka University |
Sasahara, Hampei | Tokyo Institute of Technology |
Imura, Jun-ichi | Tokyo Institute of Technology |
Oku, Makito | University of Toyama |
Aihara, Kazuyuki | University of Tokyo |
Keywords: Dynamics and control, Bioinformatics, Data mining tools
Abstract: The Dynamical Network Biomarkers (DNBs) theory has been proposed to detect early-warning signals of critical transitions in gene regulatory networks only with High-Dimension Low-Sample-Size (HDLSS) data of the system state. Towards giving a theoretical foundation for early medical treatment, this paper proposes a data-driven approach for the re-stabilization of gene regulatory networks based on HDLSS data. In the proposed re-stabilization method, only the diagonal elements of the system matrix need to be adjusted. Namely, only the self-feedback loops of mRNA expression for genes are intervened in, which reduces the complexity of the early medical treatment based on gene regulation and makes it practical to be implemented. The proposed re-stabilization method is generalized to the systems with either saddle-node bifurcation or Hopf bifurcation. Numerical simulations have been implemented to validate the effectiveness of the proposed method.
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13:50-14:10, Paper WeB18.2 | |
Introducing Organoleptic Components into Wine Fermentation Modelling: Preliminary Results |
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Philippe, Evan | UCLouvain |
David, Robert | Technord |
Dochain, Denis | Univ. Catholique De Louvain |
Mouret, Jean-Roch | INRA, Montpellier |
Keywords: Food engineering, Modeling and identification, Dynamics and control
Abstract: This paper deals with the introduction of the dynamics of some organoleptic compounds in the modelling of wine fermentation. The modelling proceeds in two steps: first the selection of the basic dynamical model (without organoleptic compounds) and the identification of its parameters, and the consideration of the five measured markers and their relation of the process variables. It is shown that those compounds that have been considered exhibits a strong relation with the CO_2 production.
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14:10-14:30, Paper WeB18.3 | |
Aroma Synthesis and Energy Consumption in Wine Fermentation: A Multiobjective Optimization Approach |
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Yabo, Agustín Gabriel | INRAE Occitanie-Montpellier |
Casenave, Céline | INRA |
Keywords: Food engineering, Dynamics and control, Scheduling, coordination, optimization
Abstract: Consumption of energy during wine fermentation process is directly linked to the temperature profile, which has also proven to have a major impact on the aromatic composition of the end product. This paper studies the impact of the temperature profile in wine fermentation, and the trade-off between the synthesis of aroma compounds and the energy required to regulate the temperature during the process. To this end, we consider a mathematical model representing the main chemical reactions of the wine fermentation including the synthesis of aromas, and a thermal model able to compute the power required to follow the temperature profile in the fermenter. The objective is to maximize the aroma concentration in the final product while minimizing the energy required to refrigerate the fermenter. The compromise between the two optimization objectives forms Pareto-optimal front solutions, and different solutions are shown in order to better understand the impact of temperature on the process. The approach intends to highlight the potential of control theory techniques and optimization to tackle the inherent cost/quality trade-offs in wine fermentation process, towards a more sustainable energy-efficient winemaking industry.
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14:30-14:50, Paper WeB18.4 | |
Predicting Microbial Cell Composition and Diauxic Growth As Optimal Control Strategies |
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Yabo, Agustín Gabriel | INRAE Occitanie-Montpellier |
Keywords: Dynamics and control, Optimal control theory, Modeling and identification
Abstract: Bacteria have evolved internal regulatory mechanisms allowing them to allocate resources to different cellular functions while dealing with the physiological limitations of the cell. In this preliminary work, we present a simple mathematical model of bacteria growing on n substitutable substrates aiming to capture these principles, focusing on the trade-off between metabolism and gene expression. The model is also able to capture a behavior known as diauxic growth, which is the sequential consumption of the nutrients in the environment resulting from the limitation of resources of the metabolic machinery. Under the hypothesis that cell regulatory mechanisms are tuned to maximize bacterial growth, we study the optimal allocation strategies through Optimal Control theory, by means of the Pontryagin's Maximum Principle. The optimal solutions are characterized by classical bang-singular-bang control structures, and can be expressed as feedback control laws, in accordance with previous results. We conclude the paper with numerical optimal trajectories of the model representing an environment with three substrates with different associated yields coefficients.
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14:50-15:10, Paper WeB18.5 | |
Data-Driven Model Predictive Control for pH Regulation in Raceway Reactors |
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Otálora, Pablo | University of Almería |
Guzman, Jose Luis | University of Almeria (Q-5450008-G) |
Gil, Juan Diego | University of Almeria |
Berenguel, Manuel | University of Almeria (CIF Q-5450008-G) |
Acién Fernández, Francisco Gabriel | University of Almeria |
Keywords: Dynamics and control, Wastewater treatment processes, Nonlinear predictive control
Abstract: The industrial production of microalgae is a highly sustainable and attractive process due to its variety of applications, especially when it is combined with wastewater treatment. From a control point of view, the optimization of the process requires a considerable effort regarding the culture conditions. The biological nature of the process renders its characterization considerably difficult, as well as the acquisition of models describing its dynamics. In this work, a complete methodology for pH control in raceway photobioreactors based on the Practical Nonlinear Model Predictive Control (PNMPC) approach is proposed. Models based on Artificial Neural Networks (ANN) of the system have been obtained and validated, and a PNMPC controller based on these data-driven models has been developed and tested in a real raceway reactor. The results demonstrate the reliability of this type of models, and justify the possibility of combining them with predictive control algorithms in highly nonlinear systems.
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15:10-15:30, Paper WeB18.6 | |
Dynamic Optimization for Monoclonal Antibody Production |
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Kaysfeld, Morten Wahlgreen | Technical University of Denmark |
Kumar, Deepak | Indian Institute of Technology Delhi |
Nielsen, Marcus Krogh | Technical University of Denmark |
Jorgensen, John Bagterp | Technical University of Denmark |
Keywords: Modeling and identification, Scheduling, coordination, optimization, Dynamics and control
Abstract: This paper presents a dynamic optimization numerical case study for Monoclonal Antibody (mAb) production. The fermentation is conducted in a continuous perfusion reactor. We represent the existing model in terms of a general modeling methodology well-suited for simulation and optimization. The model consists of six ordinary differential equations (ODEs) for the non-constant volume and the five components in the reactor. We extend the model with a glucose inhibition term to make the model feasible for optimization case studies. We formulate an optimization problem in terms of an optimal control problem (OCP) and consider four different setups for optimization. Compared to the base case, the optimal operation of the perfusion reactor increases the mAb yield with 44% when samples are taken from the reactor and with 52% without sampling. Additionally, our results show that multiple optimal feeding trajectories exist and that full glucose utilization can be forced without loss of mAb formation.
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WeB19 |
Room 419 |
Data-Based Control II |
Regular Session |
Chair: Mattsson, Per | Uppsala University |
Co-Chair: La Bella, Alessio | Politecnico Di Milano |
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13:30-13:50, Paper WeB19.1 | |
Data-Based Control Design for Nonlinear Systems with Recurrent Neural Network-Based Controllers |
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D'Amico, William | Politecnico Di Milano |
La Bella, Alessio | Politecnico Di Milano |
Dercole, Fabio | Politecnico Di Milano |
Farina, Marcello | Politecnico Di Milano |
Keywords: Data-based control, Learning for control, Stability of nonlinear systems
Abstract: This paper addresses the design of controllers for systems modelled as recurrent neural networks (RNNs). A novel data-based procedure for the design of RNN-based regulators is proposed, guaranteeing closed-loop stability properties and desired performances, conferred by virtual reference feedback tuning. The approach is tested on a realistic nonlinear system.
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13:50-14:10, Paper WeB19.2 | |
Data-Driven D-Stabilization with Performance Specifications |
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Mukherjee, Mousumi | Technical University of Kaiserslautern, Germany |
Mishra, Vikas Kumar | Vrije Universiteit Brussel (VUB) |
Bajcinca, Naim | University of Kaiserslautern |
Keywords: Data-based control, Linear systems, Data-driven robust control
Abstract: We consider the problem of designing controllers based on measurements affected by noise, for linear systems with unknown dynamics, that ensures one or more performance specifications. In particular, we consider (i) the D-stabilization problem, where performance specifications are given in terms of placing the eigenvalues of the closed-loop system in the interior of a predefined region D of the complex plane, (ii) H-infinity performance, (iii) H2 performance, and a combination of some of the above. For D-stabilization problem, a general convex region D defined by a quadratic matrix inequality (QMI) is considered. For this general region D, we provide sufficient conditions, given in terms of data-based linear matrix inequalities, for controller design. For some regions of practical interest, these conditions are necessary and sufficient. We further consider the problem of designing data-driven controllers such that multiple performance specifications, not necessarily given in terms of stability regions, are guaranteed.
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14:10-14:30, Paper WeB19.3 | |
Fast Stabilization and Identification of Unknown Linear Systems |
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Dennis Gramlich, Dennis Gramlich | RWTH Aachen University |
Ebenbauer, Christian | RWTH Aachen University |
Keywords: Adaptive control, Input and excitation design, Learning for control
Abstract: In the present work, a simple algorithm for stabilizing an unknown linear time-invariant system is proposed, assuming only that this system is stabilizable. The suggested algorithm is based on first performing a partial identification of the system and then stabilizing the controllable subsystem. It should be emphasized that our approach does not depend on any prior model knowledge and requires only a minimal number of samples.
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14:30-14:50, Paper WeB19.4 | |
Observer-Feedback-Feedforward Controller Structures in Reinforcement Learning |
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Zhang, Ruoqi | Uppsala University |
Mattsson, Per | Uppsala University |
Wigren, Torbjörn | Uppsala University |
Keywords: Controller constraints and structure, Observer design, Learning for control
Abstract: The paper proposes the use of structured neural networks for reinforcement learning based nonlinear adaptive control. The focus is on partially observable systems, with separate neural networks for the state and feedforward observer and the state feedback and feedforward controller. The observer dynamics are modelled by recurrent neural networks while a standard network is used for the controller. As discussed in the paper, this leads to a separation of the observer dynamics to the recurrent neural network part, and the state feedback to the feedback and feedforward network. The structured approach reduces the computational complexity and gives the reinforcement learning based controller an {em understandable} structure as compared to when one single neural network is used. As shown by simulation the proposed structure has the additional and main advantage that the training becomes significantly faster. Two ways to include feedforward structure are presented, one related to state feedback control and one related to classical feedforward control. The latter method introduces further structure with a separate recurrent neural network that processes only the measured disturbance. When evaluated with simulation on a nonlinear cascaded double tank process, the method with most structure performs the best, with excellent feedforward disturbance rejection gains.
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14:50-15:10, Paper WeB19.5 | |
Nonlinear Model Predictive Control: An Optimal Search Domain Reduction |
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Boggio, Mattia | Politecnico Di Torino |
Novara, Carlo | Politecnico Di Torino |
Taragna, Michele | Politecnico Di Torino |
Keywords: Nonlinear predictive control, Numerical methods for optimal control, Data-driven optimal control
Abstract: Nonlinear Model Predictive Control (NMPC) is a powerful control method, used in many industrial contexts. NMPC is based on the online solution of a suitable Optimal Control Problem (OCP) but this operation may require high computational costs, which may compromise its implementation in "fast" real-time applications. In this paper, we propose a novel NMPC approach, aiming to improve the numerical efficiency of the underlying optimization process. In particular, a Set Membership approximation method is applied to derive from data tight bounds on the optimal NMPC control law. These bounds are used to restrict the search domain of the OCP, allowing a significant reduction of the computation time. The effectiveness of the proposed NMPC strategy is demonstrated in simulation, considering an overtaking maneuver in a realistic autonomous vehicle scenario.
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15:10-15:30, Paper WeB19.6 | |
Design of a Database-Driven Controller Realized Via CMAC Memory |
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Li, Zhifeng | Hiroshima University |
Yamamoto, Toru | Hiroshima Univ |
Keywords: Data-based control, Process control, Nonlinear process control
Abstract: Proportional-integral-derivative (PID) control is widely applied in industries, though it is sometimes difficult to apply to nonlinear systems. In contrast, database-driven PID (DD-PID) control has been proposed as a control method to adjust adaptive PID parameters. However, although this method can efficiently construct control systems with high control performance for nonlinear systems, its large computational cost in terms of computation time and memory consumption limits its application to relatively slow-response systems such as some process control systems. Therefore, in this paper, the cerebellar model articulation controller (CMAC) is introduced, and a new method to realize the database constructed by DD-PID with CMAC memory is proposed. Finally, numerical simulation examples are employed to quantitatively evaluate the reduction of computation time and memory usage, which verifies the effectiveness of the proposed method.
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WeB20 |
Room 421 |
Flying Robots |
Regular Session |
Chair: Swevers, Jan | KU Leuven R&D |
Co-Chair: Nguyen, Tam Willy | University of Toyama |
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13:30-13:50, Paper WeB20.1 | |
Learning Flight Control Systems from Human Demonstrations and Real-Time Uncertainty-Informed Interventions |
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Ganesh, Prashant | University of Florida |
Ramos, Jose Humberto | University of Florida |
G. Goecks, Vinicius | Army Research Lab |
Paquet, Jared | University of Florida |
Longmire, Matthew | University of Florida |
Waytowich, Nicholas | Army Research Lab |
Brink, Kevin | Air Force Research Lab |
Keywords: Co-Learning and self-learning, Autonomous robotic systems, Flying robots
Abstract: This paper describes a methodology for learning flight control systems from human demonstrations and interventions while considering the estimated uncertainty in the learned models. The proposed approach uses human demonstrations to train an initial model via imitation learning and then iteratively, improve its performance by using real-time human interventions. The aim of the interventions is to correct undesired behaviors and adapt the model to changes in the task dynamics. The learned model uncertainty is estimated in real-time via Monte Carlo Dropout and the human supervisor is cued for intervention via an audiovisual signal when this uncertainty exceeds a predefined threshold. This proposed approach is validated in an autonomous quadrotor landing task on both fixed and moving platforms. It is shown that with this algorithm, a human can rapidly teach a flight task to an unmanned aerial vehicle via demonstrating expert trajectories and then adapt the learned model by intervening when the learned controller performs any undesired maneuver, the task changes, and/or the model uncertainty exceeds a threshold.
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13:50-14:10, Paper WeB20.2 | |
Visual Servoing Control of Quadrotors Using an Event Camera under Dim Lighting Conditions |
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Zhang, Chenxu | University of Science and Technology of China |
Di, Jian | University of Science and Technology of China |
Wang, Xinghu | University of Science and Technology of China |
Ji, Haibo | University of Science and Technology of China |
Keywords: Flying robots, Perception and sensing
Abstract: This paper studies the visual servoing control of quadrotors under dim lighting conditions. In contrast to the image-based visual servoing, we propose an event-based visual servoing scheme for quadrotors. First, we develop an asynchronous and long-lifetime eventbased corner tracking method. Then, the corner features are used to guide the quadrotor to its desired position, achieving the visual servoing under dim lighting conditions. Finally, experimental results demonstrate the superior performance of the event-based visual servoing scheme for quadrotors under dim lighting conditions.
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14:10-14:30, Paper WeB20.3 | |
Optimal and Reactive Control for Agile Drone Flight in Cluttered Environments |
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Dirckx, Dries | KU Leuven |
Bos, Mathias | KU Leuven |
Decré, Wilm | Katholieke Universiteit Leuven |
Swevers, Jan | K. U. Leuven |
Keywords: Motion control systems, Autonomous robotic systems, Flying robots
Abstract: We present a control framework for agile and reactive collision avoidance with quadrotor drones, applied to the state-based tier of the DodgeDrone Challenge, a simulation competition where the goal is to reach a finish line as fast as possible without collisions. The approach consists of an optimal control scheme with a Log-Sum-Exponential (LSE) obstacle avoidance formulation for efficient motion planning through cluttered environments with a high number of obstacles. The framework copes with a lower update frequency than required in classical Model Predictive Control by combining low-frequency smooth on-trajectory motion planning updates with computationally inexpensive high-frequency linear feedback control. This control structure is augmented with a monitoring function to allow for emergency reactive control with artificial repulsive potential fields in case of an optimal control failure to find a feasible solution in time. The approach is evaluated in extensive simulation runs, which show (1) the effectiveness of the total approach, (2) the increased added value of the LSE formulation for high numbers of obstacles, and (3) the trade-off between the execution time and the success rate. We show that our performance is competitive with the top five teams, even though the approach is, due to its model-based design, not specifically tailored to or trained for this particular challenge but is generally extendable towards other drone applications.
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14:30-14:50, Paper WeB20.4 | |
Towards a Reduced Dependency Framework for Autonomous Unified Inspect-Explore Missions |
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Kottayam Viswanathan, Vignesh | Luleå Tekniska Universitet |
Satpute, Sumeet Gajanan | Luleå University of Technology |
Agha-mohammadi, Ali-akbar | NASA-JPL, Caltech |
Nikolakopoulos, George | Luleå University of Technology |
Keywords: Robotics technology, Flying robots
Abstract: The task of establishing and maintaining situational awareness in an unknown environment is a critical step to fulfil in a mission related to the field of rescue robotics. In this article, we propose a novel approach towards the effective use of Micro Aerial Vehicles (MAVs) for obtaining a 3-D map of an unknown structure of objects. The problem is undertaken via a bifurcated approach to address the task of executing a closer inspection of detected structures with a wider exploration strategy to identify and locate nearby structures while being equipped with limited sensing capability. Predominantly, the problem of visual inspection of urban structures is dealt with view-planning based on available a-priori information. The proposed framework is evaluated experimentally in a controlled indoor environment in presence of a mock-up environment validating the efficacy of the proposed inspect-explore policy.
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14:50-15:10, Paper WeB20.5 | |
A Nullspace-Based Predictive Control Allocation for the Control of a Quadcopter Manipulating an Object Attached to the Ground |
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Nguyen, Tam Willy | University of Toyama |
Hirata, Kenji | University of Toyama |
Han, Kyoungseok | Kyungpook National University, School of Mechanical Engineering |
Keywords: Flying robots, Guidance navigation and control, Design methodologies
Abstract: In this paper, we propose a novel optimal predictive control allocation for the control of a quadcopter manipulating an object attached to the ground. This controller sprucely takes advantage of the nullspace of the quadcopter attitude mapped to the effective force to compute the optimal sequence of controls and attitude references. In particular, at each time instant, the controller solves a nonlinear minimization problem, where a specialized term is added to the cost function to penalize the deviation of the desired attitude from its nullspace, which is the attitude subspace for which any thrust generates zero effective force on the system. The weight associated to this specialized term uses a Gaussian bell-curve function to make the tuning of the attitude-reference generation more flexible and enhance the performance of the controller. To demonstrate the effectiveness of the proposed controller, numerical simulations of two different cases are provided.
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15:10-15:30, Paper WeB20.6 | |
Simulation and Initial Experiment of a Twist-Tilt Quadcopter for Fully Actuated Motion |
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Alawadhi, Abdulaziz | UCLA |
Curiel, Omar | University of California Los Angeles |
Gerber, Matthew | University of California Los Angeles |
Tsao, Tsu-Chin | University of California Los Angeles |
Keywords: Mechatronic systems, Modeling, Motion control systems
Abstract: Although conventional quadcopters are well developed and are used in many applications, they are limited to 4 degree-of-freedom motion. For instance, the underactuated quadcopters cannot hover with inclined roll or pitch angles. To achieve fully actuated 6 degreeof-freedom motion, this paper presents a design, construction, and initial experimental results of an overactuated twist-and-tilt quadcopter configuration proposed in the group’s previous work. The copter is comprised of four rotors, where each rotor’s twist and tilt angles are independently adjustable over one full rotation by servo actuators. The copter weighs 5.78kg and is designed to carry an additional 5kg payload. A comprehensive multi-body virtual plant simulation model was also created with identified parameters from the rotor-arm drive dynamics to verify the control, which is designed based on a lumped single rigid body model. Also, an experimental rig was constructed to facilitate flight testing in a small physical space with safety to both the copter and environment. The initial experimental results for 6 degree-of-freedom motion is then presented
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WeB21 |
Room 422 |
Learning and Applications |
Regular Session |
Chair: Carnerero, A. Daniel | Tokyo Institute of Technology |
Co-Chair: Reynoso-Meza, Gilberto | Pontificia Universidade Católica De Paraná |
|
13:30-13:50, Paper WeB21.1 | |
Learning-Based NMPC on SoC Platforms for Real-Time Applications Using Parallel Lipschitz Interpolation |
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Nadales, J.M. | Universidad De Sevilla |
Carnerero, A. Daniel | Tokyo Institute of Technology |
Moreno Blázquez, Carlos | University of Seville |
Haes-Ellis, Richard Mark | University of Seville |
Limon, Daniel | Universidad De Sevilla |
Keywords: Machine learning in modelling, prediction, control and automation, Real-time algorithms, scheduling, and programming, Nonlinear predictive control
Abstract: One of the main problems associated with advanced control strategies is their implementation on embedded and industrial platforms, especially when the target application requires real-time operation. Frequently, the dynamics of the system are totally or partially unknown, and data-driven methods are needed to learn an approximate model of the plant to control. On many occasions, these learning techniques use non-differentiable functions that cannot be handled by most traditional low-level gradient-based optimization methods. In addition, many data-driven techniques require the online processing of a vast amount of data, which may be exceedingly time-consuming for most real-time applications. To solve these two problems at once, we propose a low-cost solution based on a system on a chip (SoC) platform featuring an embedded microprocessor (MP) and a field programmable gate array (FPGA) to implement nonlinear model predictive control strategies. The model employed to make predictions about the future evolution of the system is learnt by means of a data-driven learning method know as parallel Lipschitz interpolation (LI) and implemented in the FPGA part. On the other hand, the optimization problem associated with the model predictive control strategy is solved by software in the MP using an adapted version of the particle swarm optimization method.
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13:50-14:10, Paper WeB21.2 | |
Complex Nonlinear System Modeling Using Type-2 Fuzzy Deep Learning |
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Francisco, Vega | CINVESTAV-IPN |
Yu, Wen | CINVESTAV-IPN |
Li, Xiaoou | CINVESTAV-IPN |
Keywords: Reinforcement learning and deep learning in control, Fuzzy and neural systems relevant to control and identification, Adaptive neural and fuzzy control
Abstract: Type-2 fuzzy systems have a great adoption in different branches of engineering, due to the fact that this type of fuzzy systems are very well suited to tasks related to nonlinear systems. Data driven models like neural networks and fuzzy systems have some disadvantages, such as the high and uncertain dimensions and complex learning process. In this paper, we show the advantages of type-2 fuzzy systems over type-1 fuzzy systems in modeling nonlinear systems. We combine Type-2 Takagi-Sugeno fuzzy model with the popular deep learning model, LSTM (long-short term memory), to overcome the disadvantages fuzzy model and neural network model. We propose a fast and stable learning algorithm for this model. Comparisons with others similar black-box and grey-box models are made, in order to show the advantages of the type-2 fuzzy LSTM neural networks.
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14:10-14:30, Paper WeB21.3 | |
Neural-Network Based Swing-Up and Stabilization Control of Rotary Inverted Pendulum Systems (I) |
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Kim, DongBeom | Hanyang University |
Nguyen, Ngo Phong | Ulsan National Institute of Science & Technology |
Moon, Jun | Hanyang University |
Keywords: Systems theory, Young engineers in control, Modelling complexity
Abstract: We propose the neural-network based control (NNC) approach for rotary inverted pendulum (RIP). The control structure for RIP consists of two phases: (i) swing-up phase, which drives the pendulum up towards the desired upright position; and (ii) stabilization phase, which enables the pendulum to keep the desired upright position. In our paper, the swing-up controller is designed based on energy control approach with feedback linearization technique, where the corresponding control gain K_{EC} is determined by the proposed NNC. Next, the stabilization controller is designed based on modified super-twisting sliding-mode control (MSTSMC) algorithm, which requires to design a new sliding surface in order to achieve the asymptotic stability of RIP. Similar to the swing-up phase, the control gain K_{SS} of the MSTSMC is determined intelligently by the proposed NNC. In fact, the proposed NNC allows to select K_{EC} and K_{SS} adaptively based on the operation of RIP. Finally, we provide the experimental comparisons between the proposed NNC and the control system of RIP without the neural-network framework. Through the experimental results, we show that by the NNC, the proposed control system of RIP provides the better swing-up and stabilization performances.
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14:30-14:50, Paper WeB21.4 | |
Dynamic Preference Learning for Complex Cobotic Tasks |
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Vella, Elena Marie | University of Melbourne |
Chapman, Airlie Jane | University of Melbourne |
Keywords: Multi-agent systems, Human robot collaboration
Abstract: In complex tasks requiring robots to collaborate with multiple human users for successful human-robot interaction, it is essential to capture user preferences in the control design. This work considers both the subjective judgements of a users preferences, to formulate a preference measure that can be used in control design. Novel to the work, is the consideration of the temporal impact that current preferences have on previously provided preferences. We formulate a weighted set-wise preference learning problem that considers the historical preferences of an individual, capturing the impact of memory on human user's preferences. We address the challenge of how to choose the best preference features as the individuals set-wise preference comparisons are sequentially presented by designing a weighted sequential preference estimator. We build upon the concept of an individual's preferences to a group of users' preferences, modelling group preferences as a normal distribution. We further extend the sequential individual preference estimation approach to multiple users' preference through the derivation of a stochastic gradient descent group preference estimator. An experimental study with 43 participants is conducted to support the proposed approaches.
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14:50-15:10, Paper WeB21.5 | |
Random Vector Functional Link Forests and Extreme Learning Forests Applied to UAV Automatic Target Recognition |
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Alves Ribeiro, Victor Henrique | Pontifícia Universidade Católica Do Paraná |
Santana Hermida, Roberto | UPV/EHU |
Reynoso-Meza, Gilberto | Pontificia Universidade Católica De Paraná |
Keywords: Machine learning, UAVs
Abstract: This paper proposes two novel machine learning algorithms, namely Random Vector Functional Link Forests and Extreme Learning Forests, to develop an improved unmanned aerial vehicles automatic target recognition system. Such models take advantage of the stochastic procedure followed by Random Forests, where random subsets of instances and features are selected to build diverse Decision Trees. However, different from the usual uni-variate split criterion from Decision Tree algorithms, we propose and employ the novel Random Vector Functional Link Tree or Extreme Learning Tree, where each decision split is performed using the fast non-linear mapping of multiple features provided by either Random Vector Functional Link or Extreme Learning Machines. To prove the efficacy of the novel algorithm, experiments are performed using 90 binary classification problems to compare the performance of the proposed algorithm against other state-of-the-art ensemble learning techniques. Statistical analysis indicates the success of the proposed algorithms in terms of both predictive performance and computational complexity. While the model with deeper trees outperforms classical ensembles in terms of predictive performance (1.41% error reduction) and has similar results to state-of-the-art ensemble models, the model with shallow trees outperforms all ensembles in terms of computational burden (at least 36% faster). Finally, the novel methods are applied to develop an automatic target recognition system for unmanned aerial vehicles, achieving a valuable trade-off in terms of area under receiver operating characteristic curve (0.9309), F1-score (0.8190), accuracy (0.8646), and computational time (4.14 s).
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15:10-15:30, Paper WeB21.6 | |
Analysis of the 3D Position Measurement of Field Fruits Via a Deep Learning and Robotic Body (I) |
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Zhang, Yanbin | Shinshu University |
Sakai, Satoru | Shinshu University |
Keywords: Plant factories, Agricultural robotics
Abstract: The paper discusses an analysis of the 3D (three-dimensional) position measurement of actual field fruits in the hand-eye coordinate system for several deep learning applications. Even though some existing papers have already discussed the analysis of the 2D position measurement of the field fruits in the image coordinate system, the 3D position measurement is needed for many operations such as selective harvesting. First, we propose a robotic vision system consisting of a stereo vision, an omnidirectional vision,and a robotic body. The stereo vision is implemented as a hand-eye and the omnidirectional vision is implemented as a base-eye. Second, we propose a measurement system consisting of a distance sensor, two angle sensors, and a tripod. Based on the fixed four points on a robotic body measurement, the 3D position of field fruits is estimated in the hand-eye coordinate system. Finally, assuming a deep learning and a heavy material handling manipulator, the measurement error is analyzed experimentally in the actual field in open outdoor. The effectiveness of the proposed vision system and the measurement system is partially confirmed.
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WeB22 |
Room 423 |
Vibration Control |
Regular Session |
Chair: Yabui, Shota | Tokyo City University |
Co-Chair: Benine-Neto, André | IMS Laboratory |
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13:30-13:50, Paper WeB22.1 | |
Modeling and Stability Analysis of Robot-Assisted Thin-Walled Milling |
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Kornmaneesang, Woraphrut | Yuan Ze University |
Tsao, Tsu-Chin | University of California Los Angeles |
Chen, Shyh-Leh | National Chung Cheng University |
Keywords: Vibration control, Robots manipulators, Stability of delay systems
Abstract: Thin-walled machining has played an important role in automotive and aerospace domains. Due to physical characteristics of the flexible structure, the thin-walled machining is prone to the deformation and the onset of chatter. To solve the problem, a robot is considered to support the flexible workpiece while cutting. This paper studies finite element dynamic modeling and stability analysis of the robot-assisted thin-walled milling system. It is divided into three submodels: thin-walled workpiece, robot, and cutting process. The finite element method (FEM) is adopted to obtain a realistic dynamic model of the workpiece and allows analysis of any location. The robot dynamics is linearized to a 1-degree-of-freedom (DOF) mass-spring-damper system for model reduction. The cutting force variation and the regenerative effects involved in the cutting process establish time-periodic and time delay terms in the milling model. The semi-discretization method (SDM) is used for the stability analysis. Simulation results show a significant improvement in the milling stability from the robot support in any location, leading to higher productivity.
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13:50-14:10, Paper WeB22.2 | |
Optimal Swing Motion Control for Single-Rod Brachiation Robot |
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Lieskovský, Juraj | Czech Technical University in Prague |
Akahane, Hijiri | Tokyo University of Agriculture and Technology |
Busek, Jaroslav | Department of Instrumentation and Control Enginnering, Faculty O |
Mizuuchi, Ikuo | Tokyo University of Agriculture and Technology |
Vyhlidal, Tomas | Czech Technical Univ in Prague, Faculty of Mechanical Engineerin |
Keywords: Vibration control, Mobile robots, Application of nonlinear analysis and design
Abstract: This paper focuses on the optimal swing and rotation control of a single-rod brachiation robot by repositioning its center of gravity. First, a time-optimal control is proposed and analyzed. It utilizes impulses of force at the robot's zero-angle and the turning-angle positions to reposition the center of gravity. Then, a practical implementation that addresses force limits is proposed, in the form of a PD controller paired with input-output linearization which uses the optimal solution as a setpoint. Both control policies are validated through simulations as a preliminary step to laboratory validation on an assembled single-rod robot. Enhanced attention is paid to energy evolution during the swing and rotation of the robot, in particular to the energy pumping achieved by repositioning the center of gravity.
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14:10-14:30, Paper WeB22.3 | |
Traveling Wave Ultrasonic Piezoelectric Motor Modelling for Automatic Headlight Position Control on Vehicles |
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El Khadri, Safouane | University of Bordeaux |
Matloub, Naji | University of Bordeaux |
Moreau, Xavier | University of Bordeaux, FRANCE |
Benine-Neto, André | IMS Laboratory |
Chevrié, Mathieu | IMS Laboratory |
Goncalves, Whilk | STELLANTIS, BCI |
Guillemard, Franck | Peugeot |
Keywords: Application of mechatronic principles, Motion control systems, Vibration control
Abstract: This work deals with some major aspects of ultrasonic traveling-wave piezoelectric motor modelling in the context of an automotive application. The aim here is to establish a proper model of this type of actuator, reflecting its behaviour. This work is a part of a larger study on the headlight automatic position control on vehicles conducted in the framework of the OpenLab “Electronics and Systems for Automotive” combining IMS laboratory and Stellantis company. The main complexity of this work is to create a proper simulator of this type of actuator, and discussing and simulating some of its behaviours, beyond what is commonly discussed in the literature, such as the direction inversion, and holding torque. Analyses are conducted on various inputs to prepare the control design.
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14:30-14:50, Paper WeB22.4 | |
Control Scheme of RRO Compensation for Track Mis-Registration in HDDs (I) |
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Yabui, Shota | Tokyo City University |
Atsumi, Takenori | Chiba Institute of Technology |
Okuyama, Atsushi | TOKAI University |
Keywords: Mechatronic systems, Motion control systems, Vibration control
Abstract: Hard disk drives (HDDs) can store large amounts of digital data, supporting an information society. The magnetic head must be precisely controlled to read/write digital data on the disk. The data were recorded as concentric orbits called tracks on a disk. The servo engineer must evaluate the track misregistration (TMR) for reliability in controller design. The TMR is one of the criteria of relative positioning accuracy for tracks for risk assessment of incorrectly written data. Risk means the magnetic heads write on a different track from the target track. The relative positioning accuracy of the tracks should be improved to decrease risk. This paper proposes a control scheme to compensate for repeatable runout (RRO) for TMR. In the proposed control system, we distinguished the RRO by "synchronous RRO" and "asynchronous RRO." Two types of RROs were compensated for using adaptive feedforward cancellation (AFC). The AFC was designed to generate a suitable compensation signal for each type of RRO, and the proposed control system improved the relative positioning accuracy. The effectiveness of the proposed scheme was verified using the HDD benchmark model developed by the IEEJ Industry Applications Society.
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14:50-15:10, Paper WeB22.5 | |
Trajectory Tracking Problem for a Flexible Mobile Manipulator: A Flatness Based Approach Combined with Active Disturbance Rejection Control |
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Feliu Talegon, Daniel | University of Castilla-La Mancha |
Sira-Ramirez, Hebertt J. | CINVESTAV-IPN |
Feliu, Vicente | Univ of Castilla-La Mancha |
Keywords: Vibration control, Mobile robots, Disturbance rejection
Abstract: This article proposes a suitable combination of Differential Flatness and Active Disturbance Rejection Control (ADRC) for the trajectory tracking problem on a flexible link mobile manipulator. The robot is composed of a flexible link (appendage) mounted on a cart and actuated at its base. A simplified virtual rigid link model, equipped with a rotational joint flexibility at the base, is proposed for modeling the nonlinear dynamics. The proposed model allows, quite realistically, to develop a robust controller on the closed loop behavior of the system. A finite element software (FEM software) is used to validate the proposed approach which simulates the dynamics of the real system. The robustness and effectiveness of the proposed control method is tested via realistic computer simulations with the FEM software, using physical parameters values obtained from an actual experimental platform. The obtained results are quite satisfactory in spite of un-modeled disturbances. Experiments, which are currently under way on an laboratory platform, will be reported elsewhere.
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15:10-15:30, Paper WeB22.6 | |
Integral Resonant Control Preserving the Rigid Body Mode of Torsional Vibration Systems |
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Yoshida, Motomu | Toyohashi University of Technology |
Gobara, Shogo | Toyohashi University of Technology |
Hiruta, Toshiki | Toyohashi University of Technology |
Inoue, Tsuyoshi | Nagoya University |
Iwasaki, Tetsuya | UCLA |
Takagi, Kentaro | Toyohashi University of Technology |
Keywords: Vibration control, Smart structures, Robust control (linear case)
Abstract: Integral resonant control (IRC) is an effective vibration control technique for flexible structures including multiple vibration modes, even though the controller is a simple first-order system. However, IRC can not be directly applied to flexible structures with rigid body modes. This paper proposes a new method to apply IRC by choosing an angle difference output in which the rigid body modes are unobservable but only elastic modes observable. The proposed method is effective for applying IRC to torsional vibration systems where the control objective is to reduce only torsional vibration modes while leaving the rigid body mode preserved. However, side effects such as an inverse response and a brake effect occur depending on the choice of the controller parameter. This paper clarifies the condition for the inverse response and the magnitude of the brake effect on the rigid body motion analytically. A new design method for the IRC controller is then presented based on the trade-off between the brake effect and the vibration suppression performance.
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WeB23 |
Room 501+502 |
Advances Toward Smart Digitized Shopfloors II |
Open Invited Session |
Chair: Macchi, Marco | Politecnico Di Milano |
Co-Chair: Cohen, Yuval | Afeka Tel Aviv College of Engineering |
Organizer: Cohen, Yuval | Afeka Tel Aviv College of Engineering |
Organizer: Macchi, Marco | Politecnico Di Milano |
Organizer: Negri, Elisa | Politecnico Di Milano |
Organizer: Faccio, Maurizio | University of Padova |
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13:30-13:50, Paper WeB23.1 | |
Clarifying Concepts of Metaverse, Digital Twin, Digital Thread and AAS for CPS-Based Production Systems (I) |
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Negri, Elisa | Politecnico Di Milano |
Abdel-Aty, Tasnim A. | Politecnico Di Milano |
Keywords: Digital twins for manufacturing, Smart manufacturing
Abstract: With the quick advent and spreading of Industry 4.0, the paradigm of Cyber Physical Systems (CPS) is becoming a reality in production systems. As the term CPS suggests, the advanced production systems are made of a digital element and a physical one that work together to reach the desired functionality. The virtual element is made of various entities that are typically generically described as “a digital representation of a physical system”. However, this general definition often is referred to terms that are actually belonging to different concepts. These terms are Metaverse, Digital Twin, Digital Thread, and Asset Administration Shell. These terms often are independently used in literature and industrial initiatives without any clear understanding of how they relate to one another or what they signify. This paper wants to contribute to the scientific discussion on these concepts and aims at analyzing their meanings and key features through a literature study, by proposing a hierarchical view on the relationships between them, their roles and functions for CPS-based production systems.
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13:50-14:10, Paper WeB23.2 | |
Anticipating Human Presence for Safer Worker - Robot Shared Workspaces (I) |
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Emmanouilidis, Christos | Univeristy of Groningen |
Elena, Rica | University of Groningen |
Duqueroie, Bertrand | THALES |
Keywords: Smart manufacturing, Intelligent manufacturing systems, Human-centric manufacturing
Abstract: The co-existence for human and mobile robots in modern industrial environments is increasingly common. Safety primitive behaviours are typically built-in mobile robots, to ensure safety. However, when fleets of multiple robots are operating in such environments, robot path planning becomes complicated and is often left sub-optimal to avoid compromising human, equipment, or process safety. Enhanced performance can be achieved if path planning takes into account not just current human presence, but projected human movement trajectories. While this problem has received extensive attention in outdoor environments in autonomous driving contexts, its indoors workspace equivalent has received less attention. This paper presents an approach for human movement prediction in industrial work environments, based on past and current heatmap occupancy grids and convolutional neural networks. The adopted heatmap format is appropriate for dealing with privacy concerns so as to avoid individual person identification. Obtained results from a range of simulation data are presented, following by a discussion on limitations, and challenges to be handled by further work.
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14:10-14:30, Paper WeB23.3 | |
Interval-Based Approach for Uncertainty Quantification of Energy Consumption Modeling in Digital Twin (I) |
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Abdoune, Farah | Nantes University |
Delumeau, Thibault | GEPEA Nantes Université, Oniris , CNRS, GEPEA, UMR 6144, F-44000 |
Nouiri, Maroua | LS2N - Nantes Université, France |
Cardin, Olivier | LS2N UMR CNRS 6004 - Nantes University - IUT De Nantes |
Keywords: Digital twins for manufacturing
Abstract: The digital twin (DT) is an emerging technology in the context of digital transformation, enabling monitoring, diagnosis, energy efficiency, and optimization of different systems. The model of DT is a crucial feature for an accurate representation of the physical system. The latter can be complex and dynamic which makes it prone to variability and stochastic behavior. Thus, the monitoring through a DT model which gives as an output a single best estimation of the nominal behavior can be sometimes insufficient considering the dynamic properties of the system. For this reason, the current paper intends to present a novel approach for DT modeling through interval models to bound and include the uncertainties inside the model using a statistical approach and Hilbert Transform. A case study is presented focusing on the energy consumption of an industrial robot considering the variability of the real process and the measurement noise.
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14:30-14:50, Paper WeB23.4 | |
An Ontology to Integrate Process-Oriented Approach in ZDM Strategies in a Digital Twin Framework (I) |
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Ghedini, Lorenzo | Politecnico Di Milano |
Polenghi, Adalberto | Politecnico Di Milano |
Macchi, Marco | Politecnico Di Milano |
Keywords: Quality assurance and maintenance, Intelligent decision support systems in manufacturing, Smart manufacturing
Abstract: The current context of Industry 4.0 is characterized by challenges that were not present in the past like greater variability, higher customization and greater complexity. To address these challenges and the increasing need from companies to focus on sustainability-related issues is necessary to adopt a quality improvement method. In this paper, the method considered is Zero Defect Manufacturing (ZDM) a “tool” which shows considerable potential, but needs some auxiliary technologies to operate. In this regard, the model proposed is an ontology based on a pre-existent ontology. This new ontology is capable of applying Detect and Repair strategies to go with the creation of a Digital Twin of the product. The realized ontology can be used to support decision-making in an industrial context: in fact, it provides to any operator in the production process, an indication about the quality of the product, also advising some corrective actions if needed, like the repair or the disassembly of the product and the subsequent recycling of the good quality components. To obtain this outcome, an analysis of the literature was performed to determine the gaps present in the literature, then an ontology editor allowed the creation of the ontology and, finally, the ontology was validated in the context of Industry 4.0 Laboratory at the Politecnico di Milano. In this environment, the proposed solution was populated with the data coming from the servers, determining the quality of the product as a function of the state of product components and the condition of one of the assets installed in the production line.
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14:50-15:10, Paper WeB23.5 | |
MAS-Based Distributed Cyber-Physical System in Smart Warehouse (I) |
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Piardi, Luis | Research Centre in Digitalization and Intelligent Robotics (CeDR |
Costa, Pedro | Faculty of Engineering University of Porto (FEUP) |
Oliveira, André Schneider | Federal University of Technology - Parana |
Leitão, Paulo | Polytechnic Institute of Bragança |
Keywords: Cyber physical system, Logistics in manufacturing, Multiagent systems
Abstract: This paper presents an approach for a multi-agent-based cyber-physical system dedicated to operating the warehouse plant with a distributed approach. The recent technological evolution has improved the quality and robustness of the services for current warehouses. However, systems that operate warehouses do not follow this evolution, presenting predominantly central monolithic or hierarchical approaches, resulting in fragility related to flexibility, scalability, and robustness in the face of disturbances. In the proposed approach, each warehouse physical component has a computational unit associated, i.e. a cyber agent, with communication, negotiation, and data analysis capabilities. Agents contain all the information, algorithms, and functions necessary to operate the physical component, and instead of receiving orders from higher-layer agents, they negotiate and collaborate to perform the tasks. The proposed system was tested in a laboratory testbed, composed of six racks and up to eight robots for transporting products. Extensive experiments show the feasibility of the approach.
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15:10-15:30, Paper WeB23.6 | |
Modeling and Control of a Cooperative Conveyance System with Multiple AGVs |
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Iori, Tomoyuki | Osaka University |
Wada, Takayuki | Osaka University |
Yoshida, Hiroshi | NEC Corporation |
Kumagai, Taichi | NEC Corporation |
Yasuda, Shinya | NEC Corporation |
Fujisaki, Yasumasa | Osaka Univ |
Keywords: Multiagent systems, Autonomous mobile robots, Modeling
Abstract: This paper presents a mathematical model of a cooperative conveyance system, where multiple AGVs transport a dolly by holding it with their holding plates. Since each holding plate can only push the dolly and cannot pull it, this asymmetry introduces discontinuity in the mathematical model. In order to keep the simplicity and scalability of the model, the asymmetry is modeled as a part of the control objective rather than a constraint, which is possible indeed in the context of model predictive control. Several numerical simulations demonstrate that cooperative conveyance with multiple AGVs can be achieved by using the proposed model.
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WeBT1 |
Hall A-1 |
Applications of Nonlinear Control |
Interactive Session |
Chair: Menini, Laura | University of Rome Tor Vergata |
Co-Chair: Yamamoto, Kaoru | Kyushu University |
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13:30-15:30, Paper WeBT1.1 | |
Multirate Predictive Control for Diode Clamped Inverters with Data-Based Learning Implementation |
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Ordonez, Joaquin G. | University of Seville |
Limon, Daniel | Universidad De Sevilla |
Gordillo, Francisco | Universidad De Sevilla |
Keywords: Power systems, Model predictive control of hybrid systems, Machine learning in modelling, prediction, control and automation
Abstract: Diode clamping is a widely used topology for power inverters due to the low number of components, low cost, and general efficiency of the circuit, but its main drawback is the difficulty in controlling a multilevel configuration. For that, finite-control-set model predictive control was chosen, as it is a multivariable optimal controller that takes into account constraints and deals with multiple objectives. However, it has high computational burden and its control solution is held constant during the sampling period if not using modulation. This work first proposes a multirate enhancement for this control technique to address the latter issue, and then uses a novel learning method to allow the online implementation and overcome the high computation time. This method is tested in simulation in a three-phase, five-level diode-clamped inverter. Comparisons and performance gains of the multirate technique are provided.
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13:30-15:30, Paper WeBT1.2 | |
Irreversible Port-Hamiltonian Modelling of 3D Compressible Fluids (I) |
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Mora, Luis A. | University of Waterloo |
Le Gorrec, Yann | FEMTO-ST, ENSMM |
Matignon, Denis | ISAE |
Ramirez, Hector | Universidad Federico Santa Maria |
Keywords: Port Hamiltonian distributed parameter systems, Thermal and process control applications of distributed parameter systems, Control of fluid flows and fluids-structures interactions
Abstract: Boundary controlled irreversible port-Hamiltonian systems (BC-IPHS) defined on 1, 2 and 3-dimensional spatial domains are defined by extending the formulation of reversible BC-PHS to irreversible thermodynamic systems controlled at the boundaries of their spatial domain. The structure of BC-IPHS has a clear physical interpretation, characterizing the coupling between energy storing and energy dissipating elements. By extending the definition of boundary port variables of BC-PHS to deal with the irreversible energy dissipation, a set of boundary port variables is defined so that BC-IPHS are passive with respect to a given set of conjugated inputs and outputs. As for finite-dimensional IPHS and 1-D infinite-dimensional IPHS recently defined in [Ramirez et al., Chem. Eng. Sci. (2022)], the first and second laws of Thermodynamics are satisfied as a structural property of the system. As a common thread, the 3D compressible fluid example is worked out to illustrate the proposed approach: both the reversible case of the isentropic fluid and the irreversible case of the non-isentropic fluid are presented.
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13:30-15:30, Paper WeBT1.3 | |
Adaptive Fixed-Time Anti-Synchronization of Neural Networks: Potential Application in Active Noise Control |
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Li, Haoyu | China University of Geosciences, Wuhan |
Wang, Leimin | China University of Geosciences |
Keywords: Application of nonlinear analysis and design, Adaptive control, Lyapunov methods
Abstract: This paper discusses active noise control (ANC) through the dynamics analysis of neural networks. By designing an adaptive controller on the controlled neural network to generate a signal opposite to the noise source, the latter is considered neural networks with unknown parameters. To leave only the propagating signal sources in the channel, the controlled neural network is achieved the anti-synchronization with the unknown parameter neural network (fitted to noise source). Considering different noise environments, fixed-time control is introduced in ANC, i.e., the fixed-time stability of the error system is proved by the Lyapunov method. Since NNs-based ANC can directly obtain the anti-signal, our control scheme can significantly simplify the existing ANC scheme. Finally, a simulation example is provided to demonstrate the feasibility of the results in this paper.
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13:30-15:30, Paper WeBT1.4 | |
Nonlinear Sampled-Data Systems - a Lifting Framework |
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Yamamoto, Yutaka | Kyoto University |
Yamamoto, Kaoru | Kyushu University |
Keywords: Application of nonlinear analysis and design, Sampled-data control, Control of switched systems
Abstract: This short note gives a new framework for dealing with nonlinear sampled-data systems. We introduce a new idea of lifting, which is well known for linear systems, but not successfully generalized to nonlinear systems. This paper introduces a new lifting technique for nonlinear, time-invariant systems, which are different from the linear counterpart as developed by, e.g., Bamieh et al. and Yamamoto, etc. The main difficulty is that the direct feedthrough term effective in the linear case cannot be generalized to the nonlinear case. Instead, we will further lift the state trajectory, and obtain an equivalent time-invariant discrete-time system with function-space input and output spaces. The basic framework, as well as the closed-loop equation with discrete-time controller, is given. As an application of this framework, we give a representation for the Koopman operator derived from the given original nonlinear system.
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13:30-15:30, Paper WeBT1.5 | |
On the Pull-In and Hold-In Ranges of Type 1 PLL with Piecewise-Linear Phase Detector Characteristic |
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Kuznetsov, Nikolay | Saint-Petersburg State Univ |
Lobachev, Mikhail | Saint Petersburg State University |
Yuldashev, Marat | Saint Petersburg State University |
Yuldashev, Renat | St. Petersburg State University |
Keywords: Application of nonlinear analysis and design, Stability of nonlinear systems, Lyapunov methods
Abstract: In the present work, we consider a special case of a second-order system of ordinary differential equations which describes dynamics of a synchronization circuit called a phase-locked loop (PLL). A lead-lag loop filter and a piecewise-linear phase detector characteristic are considered resulting the final model to be a type 1 PLL. The stability and synchronization properties of the loop are characterized by so-called hold-in range and pull-in range, which describe set of parameters providing local stability of equilibria and global stability of the system, respectively. In this article, we determine the set of loop parameters such that the pull-in and hold-in ranges coincide.
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13:30-15:30, Paper WeBT1.6 | |
On Hyperexponential Stabilization of Double Integrator in Continuous and Discrete Time |
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Efimov, Denis | Inria |
Polyakov, Andrey | INRIA Lille Nord-Europe |
Zimenko, Konstantin | ITMO University |
Wang, Jian | Hangzhou Dianzi University |
Keywords: Application of nonlinear analysis and design, Robust control (linear case), Input-to-state stability
Abstract: A time-varying state feedback is presented that guarantees stability with hyperexponential rate of convergence of all trajectories to the origin for a double integrator system. It is shown that this convergence property is uniform with respect to matched bounded external disturbances. An implicit time-discretization scheme of the closed-loop system is given, which preserves all main properties of the continuous-time counterpart, and in addition has bounded errors with respect to the measurement noises. Based on this discretization, for sampled-and-hold implementation, a modified linear time-varying state feedback is proposed providing an accelerated rate of convergence to the continuous-time plant. The efficiency of the suggested control is illustrated through numeric experiments.
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13:30-15:30, Paper WeBT1.7 | |
Finite Dimensional Koopman Form of Polynomial Nonlinear Systems |
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Iacob, Lucian Cristian | Eindhoven University of Technology |
Schoukens, Maarten | Eindhoven University of Technology |
Tóth, Roland | Eindhoven University of Technology |
Keywords: Application of nonlinear analysis and design
Abstract: The Koopman framework is a popular approach to transform a finite dimensional nonlinear system into an infinite dimensional, but linear model through a lifting process using so-called observable functions. While there is an extensive theory on infinite dimensional representations in the operator sense, there are few constructive results on how to select the observables to realize them. When it comes to the possibility of finite Koopman representations, which are highly important from a practical point of view, there is no constructive theory. Hence, in practice, often a data-based method and ad-hoc choice of the observable functions is used. When truncating to a finite number of basis, there is also no clear indication of the introduced approximation error. In this paper, we propose a systematic method to compute the finite dimensional Koopman embedding of a specific class of polynomial nonlinear systems in continuous-time, such that the embedding can fully represent the dynamics of the nonlinear system without any approximation.
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13:30-15:30, Paper WeBT1.8 | |
Full State Feedback Linearization for a Haulage Trolley System: A Novel Differentiable Manifold Approach |
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Ngwako, Mohlalakoma Therecia | Wits University |
Ekoru, John Elisa Dimiti | University of the Witwatersrand |
Madahana, Milka Cynthia Ijunga | Witwatersrand University |
Nyandoro, Otis Tichatonga | University of the Witwatersrand, Johannesburg |
Keywords: Application of nonlinear analysis and design, Nonlinear and optimal automotive control, Rail transportation modelling and control systems
Abstract: The manuscript presents a manifold-based full-state linearization for a haulage trolley. The key result from the manifold approach is representing the linearized system as a function of the tangent vectors of the nonlinear system. The haulage trolley is linearized, and the system's performance is studied. Three case studies are interrogated; the nonlinear system, a regulator control problem, and a tracking control problem. A settling time of 2 s is set for the control problem, and a reference is set to 1 rad/s for the tracking problem. The results confirm that linear control methods work on the controllable linearized haulage trolley system.
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13:30-15:30, Paper WeBT1.9 | |
Test Bed Emulation of Secondary Loop Refrigeration Units Using Peltier Elements: An Impedance Control Approach |
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Fallmann, Markus | TU Wien |
Kölbl, Julian | TU Wien |
Ausweger, Tobias | TU Wien |
Lösch, Maximilian | TU Wien |
Poks, Agnes | TU Wien |
Kozek, Martin | Vienna University of Technology |
Keywords: Energy systems, Digital implementation, Robust controller synthesis
Abstract: Advanced control methods help to increase the efficiency of refrigerated applications, easing their economic and ecological burden. However, approaches from literature have rarely been validated experimentally. One significant reason is the high expenses when conducting control experiments on full-sized plants. Low-maintenance, low-cost testing facilities constitute a possible remedy. Therefore, this work proposes a test bed refrigeration unit based on Peltier elements, for which impedance control compensates the behavioral differences to an actual secondary loop refrigeration unit. The two-degree-of-freedom control architecture comprises a static feedforward and a PID path that is robustified by choosing a linear design model based on the nu-gap metric. Experimental validation using a 260 min cycle shows that the achieved system trajectory lies within sensor accuracy to the desired one for more than 99% of the time, proving adequate emulation. Thus, the proposed concept is suitable to experimentally investigate highlevel temperature control algorithms for refrigerated applications.
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13:30-15:30, Paper WeBT1.10 | |
Object-Oriented Modelling of Advanced Computer Cooling Solutions |
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Leva, Alberto | Politecnico Di Milano |
Terraneo, Federico | Politecnico Di Milano |
Cancelliere, Tobia | Politecnico Di Milano (former Graduate Student) |
Chioggi, Marco | Politecnico Di Milano (graduate Student) |
Fornaciari, William | Politecnico Di Milano |
Atienza, David | EPFL Lausanne |
Keywords: Energy systems
Abstract: Modern computing systems are so energy-intensive to make efficient cooling vital for their operation. This is giving rise to a variety of innovative cooling solutions based on a mix of traditional and new techniques. The design and engineering of these solutions, as well as of the necessarily involved controls, requires dynamic simulation. Cooling simulation models must be capable of representing multi-physics cyber-physical systems, of connecting to specialised 3D chip simulators when high detail is needed, and at the same time of scaling up to the data centre -- tailoring the detail level accordingly -- when system-level studies need carrying out. In such a challenging emph{scenario}, an enabling technology is Object-Oriented Modelling (OOM). Along this approach we here present a Modelica library to serve the purposes just outlined, and that we are releasing as free software for the scientific and engineering community.
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13:30-15:30, Paper WeBT1.11 | |
Modeling and Passivity Properties of Multi-Producer District Heating Systems |
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Machado Martinez, Juan Eduardo | University of Groningen |
Cucuzzella, Michele | University of Pavia |
Scherpen, Jacquelien M.A. | University of Groningen |
Keywords: Energy systems, Networked systems, Passivity-based control
Abstract: We propose a comprehensive nonlinear ODE-based thermo-hydraulic model of a district heating system featuring several heat producers, consumers and storage devices which are interconnected through a distribution network of meshed topology whose temperature dynamics are explicitly considered. Moreover, we analyze the conditions under which the hydraulic and thermal subsystems of the model exhibit shifted passivity properties. For the hydraulic subsystem, our claims on passivity draw on the monotonicity of the vector field associated to the district heating system’s flow dynamics, which mainly codifies viscous friction effects on the system’s pressures. For the temperature dynamics, we propose a storage function based on the ectropy function of a thermodynamic system, recently used in the passivity analysis of heat exchanger networks.
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13:30-15:30, Paper WeBT1.12 | |
An Implicit Feedforward MPC Coordinated Control for Parabolic Trough CSP Systems with Indirect Thermal Energy Storage |
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Wang, Jiaxing | Southeast University |
Li, Yiguo | Southeast University |
Zhang, Junli | Southeast University |
Pan, Lei | Southeast University |
Liu, Zhenxiang | Southeast University |
Keywords: Predictive control, Energy systems, Disturbance rejection
Abstract: Solar thermal power systems have an intermittent and uncertain energy source, solar irradiance, compared to conventional thermal power plants. Solar irradiance disturbances pose a great challenge to the safe operation and power stability of concentrated solar power (CSP) systems. The coordinated control strategy of the whole system is designed based on the centralized model predictive control (MPC) method. An implicit feedforward prediction model that relates the irradiance disturbance dynamics to the process output is used, enabling reasonable compensation for disturbances in the process output without the need for a separate feedforward controller. The simulation results show that the stability of the outputs of the CSP systems is ensured during solar irradiance disturbances with the proposed implicit feedforward MPC.
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13:30-15:30, Paper WeBT1.13 | |
Energy-Balancing Dual-Port Grid-Forming Control for VSC-HVDC Systems |
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Subotic, Irina | ETH Zurich |
Gross, Dominic | University of Wisconsin-Madison |
Keywords: Power systems, Power systems stability
Abstract: This work examines energy-balancing dual port grid-forming (GFM) control for high-voltage direct current (HVDC) transmission. In contrast to the state-of-the art, HVDC converters controlled in this way do not require assigning GFM and grid-following roles to different converters. Moreover, this control enables primary frequency control and inertia support through HVDC links. A detailed stability and steady-state analysis results in conditions on the control gains such that i) the overall hybrid dc/ac system is stable, ii) asynchronous ac areas are quasi-synchronous, and iii) circulating power in cyclic topologies is avoided. Finally, a high-fidelity case study is used to illustrate and verify the analytical results.
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13:30-15:30, Paper WeBT1.14 | |
Dissipativity of Nonlinear ODE Model of Distribution Voltage Profile |
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Kojima, Chiaki | Toyama Prefectural University |
Muto, Yuya | Toyama Prefectural University |
Susuki, Yoshihiko | Kyoto University |
Keywords: Power systems, Passivity-based control, Modeling and simulation of power systems
Abstract: In this paper, we consider a power distribution system consisting of a straight feeder line. A nonlinear ordinary differential equation (ODE) model is used to describe the voltage distribution profile over the feeder line. At first, we show the dissipativity of the subsystems corresponding to active and reactive powers. We also show that the dissipation rates of these subsystems coincide with the distribution loss given by a square of current amplitudes. Moreover, the entire distribution system is decomposed into two subsystems corresponding to voltage amplitude and phase. As a main result, we prove the dissipativity of these subsystems based on the decomposition. As a physical interpretation of these results, we clarify that the phenomena related to the gradients of the voltage amplitude and phase are induced in a typical power distribution system from the dissipation equalities. Finally, we discuss a reduction of distribution losses based on the dissipation rate of the subsystem of voltage amplitude.
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WeBT2 |
Hall A-2 |
Biomedical Systems |
Interactive Session |
Chair: Kovacs, Levente | Obuda University |
Co-Chair: Furutani, Eiko | Univ. of Hyogo |
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13:30-15:30, Paper WeBT2.1 | |
Pre-Disease Detection Using Dynamical Network Biomarkers in Gene Regulatory Networks with Cell-To-Cell Interaction |
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Saito, Yuto | Tokyo Institute of Technology |
Sasahara, Hampei | Tokyo Institute of Technology |
Shen, Xun | Osaka University |
Pena Ramirez, Jonatan | Center for Scientific Research and Higher Education at Ensenada |
Imura, Jun-ichi | Tokyo Institute of Technology |
Oku, Makito | University of Toyama |
Aihara, Kazuyuki | University of Tokyo |
Keywords: Kinetic modeling and control of biological systems, Fault diagnosis, Bio-signals analysis and interpretation
Abstract: Dynamical Network Biomarkers (DNB) theory has been proposed as a method for detecting diseases at a very early stage. The progression of a disease can be regarded as a bifurcation phenomenon of the underlying dynamical system associated with the corresponding gene network. By identifying large fluctuations of the gene expression level occurring just before the bifurcation, we can detect the pre-disease stage without identifying the mathematical model of the dynamical system. However, the existing DNB theory mainly focuses on a single gene network representing averaged dynamics of multiple cells not explicitly handling a group of cells with cell-to-cell interaction. In this study, we extend the DNB theory to the case where cell-to-cell interaction is also taken into account. Ultimately, our analysis reveals that the pre-disease stage can be detected from the observation of the average gene expression when the bifurcation is induced by the intrinsic dynamics of the cells, whereas it remains undetectable when the bifurcation is produced by the interaction.
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13:30-15:30, Paper WeBT2.2 | |
Scheduling Dosage of Proton Pump Inhibitors Using Constrained Optimization with Gastric Acid Secretion Model |
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Li, Yutong | University of Michigan, Ann Arbor |
Li, Nan | University of Michigan |
Girard, Anouck | University of Michigan, Ann Arbor |
Kolmanovsky, Ilya V. | University of Michigan |
Keywords: Decision support and control, Control of physiological and clinical variables
Abstract: Dosage schedule of the Proton Pump Inhibitors (PPIs) is critical for gastric acid disorder treatment. In this paper, we develop a constrained optimization based approach for scheduling the PPIs dosage. In particular, we exploit a mathematical prediction model describing the gastric acid secretion, and use it within the optimization algorithm to predict the acid level. The dosage of the PPIs which is used to enforce acid level constraints is computed by solving a constrained optimization problem. Simulation results show that the proposed approach can successfully suppress the gastric acid level with less PPIs intake compared with the conventional fixed PPIs dosage regimen, which may reduce the long-term side effects of the PPIs.
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13:30-15:30, Paper WeBT2.3 | |
Towards a Controlled Orthosis for Sit-To-Stand Support in Independently Living Elderly: Model Development |
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Juchem, Jasper | Ghent University |
Loccufier, Mia | Ghent Univ |
Chevalier, Amélie | Ghent University |
Keywords: Rehabilitation engineering and healthcare delivery, Biomedical system modeling, simulation and visualization, Control of voluntary movements, respiration
Abstract: Sit-to-stand (STS) movements are a daily challenge for independently living elderly. Literature shows a keen interest in using active orthoses to mitigate this problem. However, to design and test advanced control strategies for proof-of-concept orthoses, a validated model of the STS movement is missing. This work presents and elaborates on a model of the kinematics of the lower limb in combination with a human policy which represents the brain-muscle interaction. The model parameters are derived from both healthy and elderly patients. The applicability of the model is investigated by applying two popular control methods for active orthoses: gravity compensation and a control-based method. First, the results show model validation using measured in vivo joint torques from literature and, second, that both methods can be simulated using the developed STS model. This allows for optimizing and testing advanced control strategies in future work.
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13:30-15:30, Paper WeBT2.4 | |
Towards End-To-End Automated Microscopy Control Using Holotomography: Workflow Design and Data Management |
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Zwirnmann, Henning | Technical University of Munich, Munich Institute of Robotics And |
Knobbe, Dennis | Technical University of Munich (TUM) |
Haddadin, Sami | Technical University of Munich |
Keywords: Biomedical and medical image processing and systems, Bio-signals analysis and interpretation, Bioinformatics
Abstract: Microscopy has been a key tool involved in many discoveries in the life sciences over the past centuries. In the last 30 years in particular, enormous progress has been made in developing this measurement technique further to make researchers working with it more effective. To combine gains in reproducibility and efficiency resulting from these advancements in different research areas, we present for the first time a unified and comprehensive concept for an end-to-end automated microscopy workflow. To this end, we employ both robotic and computational methods as well as holotomography microscopy. Considering the physical preparation and cleanup of a measurement, the image acquisition, and the management and analysis of the resulting data, we give a fine-grained workflow description. We present the robotic system to perform the manual process steps and a Python package to standardize the resulting proprietary image (meta)data. For the other tasks, we identify suitable open-source tools to execute them and apply them to our setup. The choice of holotomography as a suitable microscopy technique to realize this workflow is elucidated. We envision that the adoption of an automated workflow paves the way toward a future life science laboratory where microscopy-based research is carried out more efficiently and reproducibly than in the past.
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13:30-15:30, Paper WeBT2.5 | |
Actively Controlled Cardiac Afterload |
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Pigot, Henry | Lund University |
Wahlquist, Ylva | Lund University |
Soltesz, Kristian | Lund University |
Keywords: Artificial pancreas or organs, Control of physiological and clinical variables, Physiological Model
Abstract: Ex vivo (outside of the body) working heart models enable the evaluation of isolated hearts. They are envisioned to play an important role in increasing the currently low utilization rate of donor hearts for transplantation. For the heart to work in isolation, an afterload (flow impedance) is needed. To date, afterload devices have been constructed by combining multiple constituent elements such as pumps, flow resistances, and flow capacitances (compliances), typically to replicate the structure of so-called Windkessel models. This limits active control to that achievable by varying these elements, making it slow and subject to the problem of dynamic coupling between parameters. Here we present a novel concept to achieve Windkessel dynamics through a very simple variable flow impedance. The impedance is actively controlled using feedback from a pressure measurement. Through simulations we demonstrate the ability to perfectly emulate Windkessel dynamics, while imposing tight pressure limits needed for safe operation—something not achievable with the verbatim implementation using constituent elements.
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13:30-15:30, Paper WeBT2.6 | |
Towards Closing the Loop in Depth-Of-Hypnosis Control: Connecting Matlab-Simulink to Medical Devices |
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Karer, Gorazd | University of Ljubljana |
Keywords: Control of physiological and clinical variables, Pharmacokinetics and drug delivery, Remote sensor data acquisition
Abstract: When performing a diagnostic procedure or a surgical intervention under general anesthesia (GA), the correct induction and dosage of anesthetic drugs is one of the principal objectives of the anesthesiologist. An important aspect is the depth of hypnosis (DoH), which seems a suitable process for the implementation of closed-loop control. To implement such a system, we must be able to acquire signals from a patient monitor in real time, determine the appropriate control signal, and relay the control signal to an infusion pump. However, many patient monitors and infusion pumps are not able to connect to an external (possibly medically unapproved) device during a procedure, making closed-loop control impossible. In this paper, we propose a solution to the problem of connecting medical devices to a computer. First, a universal noninvasive image-based system for signal acquisition from a patient monitor enables the acquisition of DoH measurement in Matlab-Simulink. Second, a serial-communication-based method is used to transmit the calculated anesthetic inflow value to the infusion pump. The whole system is based on Matlab-Simulink environment so that it can be conveniently used and extended for advanced DoH modelling, simulation, and control. The feasibility of the proposed framework was tested both in a simulated GA environment and in a real operating theater during lumbar spine surgery. The tests have shown that the system works reliably and can therefore be a useful basis for implementing new algorithms for closed-loop control of DoH.
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13:30-15:30, Paper WeBT2.7 | |
Optimized Motor Imagery Paradigm Via Multimodal Stimulation and Explainable LSTM Model in fNIRS-Based BCI |
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Huang, Yuzhu | South China University of Technology |
Yu, Zhuliang | South China University of Technology |
Gu, Zhenghui | South China University of Technology |
Xie, Xiaofeng | Hainan University |
Tang, Rongnian | Hainan University |
Li, Chuang | Hainan University |
Keywords: Rehabilitation engineering and healthcare delivery, Biomedical system modeling, simulation and visualization, Bio-signals analysis and interpretation
Abstract: Motor imagery-based brain--computer interface (MI-BCI) has been applied in the field of motor function rehabilitation for the improvement of patients’ motor function. Functional near-infrared spectroscopy (fNIRS) can be used to study the working mechanism of the brain by monitoring hemodynamic responses related to the activation of cortical neurons. Hence, a novel MI-fNIRS-BCI system with multimodal stimulation is proposed. The multimodal stimulation paradigms include ``visual-auditory stimulation,'' ``electrical stimulation + proprioceptive stimulation,'' and ``visual-auditory stimulation + electrical stimulation + proprioceptive stimulation.'' We explored the optimization of the combination of various stimulations to enhance motor imagery patterns. Furthermore, an explainable long short-term memory (e-LSTM) model was designed to decode cortical activation. The motor imagery task was classified using an LSTM network and the relationship between the classification results and cortical activation was analyzed using an explanation module. Comparative experiments were conducted with eight healthy subjects. The results demonstrated that classification accuracies were significantly improved in the multimodal stimulation paradigms. The proposed MI-fNIRS-BCI system can improve the motor imagery patterns and enhance cortical activation during motor imagery.
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13:30-15:30, Paper WeBT2.8 | |
Experiment Design Considerations for Estimating Energy Expenditure During Wheelchair Propulsion |
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Doshmanziari, Roya | Norwegian University of Science and Technology |
Aandahl, Håkon Strand | Nord University |
Lyng Danielsson, Marius | Norwegian University of Science and Technology |
Baumgart, Julia Kathrin | Norwegian University of Science and Technology |
Varagnolo, Damiano | NTNU - Norwegian University of Science and Technology |
Keywords: Model formulation, experiment design, Bio-signals analysis and interpretation, Physiological Model
Abstract: We propose a methodology for estimating energy expenditure (EE) during wheelchair propulsion. The method is based on measured physiological and kinematic signals from wearable sensor devices in an experimental setup design. More specifically, we have developed regression models based on features extracted from heart rate, acceleration and gyroscope data collected during nine experiment stages with twenty participants. Support Vector regression and Gaussian process regression methods were implemented to provide an estimate of EE for each participant during the experiment. Extensive cross validation techniques were applied to evaluate the performance of the proposed models and investigate the necessity of personalizing the algorithms based on personal characteristics.
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13:30-15:30, Paper WeBT2.9 | |
Direct Estimation of Linear Filters for EEG Source-Localization in a Competing-Talker Scenario |
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Wilroth, Johanna | Linköping University |
Kulasingham, Joshua Pranjeevan | Linköping University |
Skoglund, Martin A | Linköping University |
Alickovic, Emina | Eriksholm Research Centre |
Keywords: Bio-signals analysis and interpretation, Brain-machine interaction, Time series modelling
Abstract: Hearing-impaired listeners have a reduced ability to selectively attend to sounds of interest amid distracting sounds in everyday environments. This ability is not fully regained with modern hearing technology. A better understanding of the brain mechanisms underlying selective attention during speech processing may lead to brain-controlled hearing aids with improved detection and amplification of the attended speech. Prior work has shown that brain responses to speech, measured with magnetoencephalography (MEG) or electroencephalography (EEG), are modulated by selective attention. These responses can be predicted from the speech signal through linear filters called Temporal Response Functions (TRFs). Unfortunately, these sensor-level predictions are often noisy and do not provide much insight into specific brain source locations. Therefore, a novel method called Neuro-Current Response Functions (NCRFs) was recently introduced to directly estimate linear filters at the brain source level from MEG responses to speech from one talker. However, MEG is not well-suited for wearable and real- time hearing technologies. This work aims to adapt the NCRF method for EEG under more realistic listening environments. EEG data was recorded from a hearing-impaired listener while attending to one of two competing talkers embedded in 16-talker babble noise. Preliminary results indicate that source-localized linear filters can be directly estimated from EEG data in such competing-talker scenarios. Future work will focus on evaluating the current method on a larger dataset and on developing novel methods, which may aid in the improvement of next- generation brain-controlled hearing technology.
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13:30-15:30, Paper WeBT2.10 | |
Model Identification with Incomplete Input Data in Type 1 Diabetes |
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Ozaslan, Basak | Harvard University |
Aiello, Eleonora Maria | Harvard University |
Doyle, Francis | Harvard University |
Dassau, Eyal | Harvard University |
Keywords: Identification and validation, Quantification of physiological parameters for diagnosis and treatment assessment, Grey box modelling
Abstract: A major challenge in fitting models to glucose metabolism in people with type 1 diabetes is incomplete data as its collection partially relies on self-reporting and does not include all relevant events. We develop a method for identifying optimal input corrections to reestablish a correct input-output relationship in the data while jointly identifying personalized model parameters. The unreported or misreported parts in the data are reconciled by adding sparse corrections via mixed-integer quadratic programming leading to an improved identification of the model parameters. We conduct numerical experiments with incomplete in-silico training data and show that models obtained from our method are able to provide more accurate predictions on test data than models obtained from standard methods. The performance of our methodology is similar to that attained with the standard method when trained on data with complete information.
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13:30-15:30, Paper WeBT2.11 | |
A Minimal Model for Type-1 DM Patients: Meal and Exercise Adaptation |
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Chandrasekhar, Abishek | Indian Institute of Science |
Padhi, Radhakant | Indian Institute of Science |
Keywords: Artificial pancreas or organs, Biomedical system modeling, simulation and visualization, Physiological Model
Abstract: Mathematical Modeling of glucose-insulin dynamics of Type-1 Diabetic Mellitus (T1DM) patients is an essential component of the design and development of Artificial Pancreas Systems. These model parameters, which exhibit significant inter-patient variability, are identified for each individual T1DM patient through standard tolerance tests. However, in addition to the inter-patient variability, each patient's model parameters vary according to the circadian rhythm. Therefore, the blood glucose response to a meal is different at breakfast when compared to lunch and dinner. In addition to this, the glucose-insulin dynamics vary when the T1DM patient exercises or during any physical activity. To account for these intra-patient variabilities and the variability due to exercise, a neuro-adaptive learning scheme is proposed in this work. The uncertainties are approximated as a product of a weight and a meaningful basis function. The model uncertainties are learned during meals and idle activity, whereas exercise learning requires an announcement from the patient and is only learned when the patient is exercising. This neuroadaptive learning scheme can prove to be of vital importance in designing model-based control laws for blood glucose regulation in Type-1 Diabetic patients.
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13:30-15:30, Paper WeBT2.12 | |
Nonlinear Model Predictive Control of Vagal Nerve Stimulation to Regulate Hemodynamic Variables |
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Adeodu, Oluwasanmi | Lehigh University |
Gee, Michelle M. | University of Delaware |
Mahmoudi, Babak | Emory University |
Vadigepalli, Rajanikanth | Thomas Jefferson University |
Kothare, Mayuresh V. | Lehigh Univ |
Keywords: Control of physiological and clinical variables, Kinetic modeling and control of biological systems, Control in neuroscience
Abstract: Various pre-clinical investigations indicate that the electrical stimulation of the cervical branch of the vagus that innervates the heart has therapeutic value in the management of various cardiac diseases. In theory, the design of a closed-loop control mechanism that automatically adjusts vagal nerve stimulation (VNS) parameters based on real-time physiological feedback can eliminate intra-patient variability in VNS outcomes and therefore represents a major step towards patient-specific therapy. This study develops a nonlinear model predictive control (NMPC) approach for VNS of a pulsatile, human cardio-baroreflex system. The manipulated variables are the frequency and amplitude of a charge-balanced biphasic current. The effects of these variables on hemodynamic quantities such as heart rate, blood pressure, heart contractility e.t.c. are estimated under the assumption that the desired activation of efferent vagal nerve fibers within the vagosympathetic complex can not be realistically isolated from the off-target activation of afferent fibers. An approximate, cycle-averaged cardiovascular model is derived to eliminate pulsatility and is used for prediction in the controller. The feasibility of this NMPC scheme is explored with a set-point tracking example.
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13:30-15:30, Paper WeBT2.13 | |
Control Lyapunov-Barrier Function Based Stochastic Model Predictive Control for COVID-19 Pandemic |
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Zheng, Weijiang | Beihang University |
Zhu, Bing | Beihang University |
Ye, Xianming | University of Pretoria |
Zuo, Zongyu | Beijing University of Aeronautics and Astronautics |
Keywords: Decision support and control, Dynamics and control, Nonlinear predictive control
Abstract: In this paper, a stochastic model predictive control (MPC) is proposed to design a non-pharmacutical policy to control and prevent the COVID-19 pandemic. The system dynamics of COVID-19 is described by a stochastic SEIHR model subject to practical constraints, and the model is proved to be feedback linearizable. A stochastic Control Lyapunov-Barrier Function (CLBF) is constructed for the feedback linearizable system. Constraints on hospitalized individuals are regarded as the unsafe region to construct the corresponding stochastic CLBF. In the proposed stochastic MPC, the stochastic CLBF constraints are applied to improve the overall performance on controlling and preventing the epidemic. Both theoretical proof and simulation results imply that, with the CLBF-based stochastic MPC, the proposed policy is effective in controlling and preventing COVID-19 pandemic.
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WeBT3 |
Hall A-3 |
Manufacturing Plant Modelling and Control I |
Interactive Session |
Chair: Iung, Benoît | Lorraine University |
Co-Chair: Okajima, Hiroshi | Kumamoto University |
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13:30-15:30, Paper WeBT3.1 | |
Additive or Conventional Manufacturing As Spare Parts Manufacturing Technology: The Impact of Qualification Tests (I) |
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Peron, Mirco | NTNU |
Cantini, Alessandra | University of Florence |
Coruzzolo, Antonio Maria | University of Modena and Reggio Emilia |
Keywords: Additive manufacturing, Quality assurance and maintenance
Abstract: Additive manufacturing (AM) has recently emerged as a potential breakthrough technology in the world of spare parts management. Thanks to its characteristics, it can enable the production of spare parts with very low production lead time, with considerable impacts in terms of inventory levels. Some researchers have recently focused on the topic, trying to understand whether it is convenient to produce spare parts in AM or in Conventional Manufacturing (CM) techniques. However, all these works are neglecting a crucial aspect. Spare parts, before being utilized, need to be qualified from certified entities. The qualification requirements vary depending on the criticality of the spare parts, but they are all associated with non-negligible costs, which however have been completely neglected so far. In this work, to overcome this gap we develop a mathematical model that can support managers and practitioners in choosing the most convenient manufacturing technology (i.e. AM or CM) considering for the first time the qualification costs. The model proposed has been applied to a real case study to demonstrate its applicability.
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13:30-15:30, Paper WeBT3.2 | |
Decision Considerations for Securing and Managing Intellectual Property within Additive Manufacturing Supply Chains (I) |
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Adu-Amankwa, Kwaku | University of Strathclyde |
Rentizelas, Athanasios | National Technical University of Athens |
Daly, Angela | University of Dundee |
Corney, Jonathan | University of Edinburgh |
Wodehouse, Andrew | University of Strathclyde |
Peron, Mirco | NTNU |
Keywords: Additive manufacturing, Supply chain management , Modelling and decision making in complex systems
Abstract: Intellectual property is a crucial asset that generates debates about its effects on additive manufacturing supply chains. Actors within these supply chains must adapt to navigate intellectual property issues and decisions to sustain growth. However, no consensus exists among scholars and practitioners on “whether, why, or how” to secure and manage intellectual property, which complicates decision-making. This paper presents a quantitative survey of expert opinions from management, engineering, academia, and consultancy sectors on various decision considerations for securing and managing intellectual property in additive manufacturing supply chains. The findings indicate that decision-making remains significantly complex and non-uniform; this offers insights into crucial considerations when aiming to secure or manage intellectual property as a valued and balanced asset in additive manufacturing supply chains.
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13:30-15:30, Paper WeBT3.3 | |
Thermal Images and Temperature Matrices for the State Assessment of Rolling Bearings (I) |
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Gómez Benavides, Edgar Daniel | Universidad De Los Andes |
Barbieri, Giacomo | Universidad De Los Andes |
Keywords: Prognostics & health management, Maintenance engineering and management, Industry 4.0
Abstract: The assessment of the health state of rolling bearings is important for supporting the decision-making concerning their maintenance and operation. Even if different techniques and methods have been utilized, approaches based on Infrared Termography (IRT) have not been sufficiently explored. In this paper, the potential that IRT may have for classifying the severity of failures of rolling bearings is investigated. This study compares different approaches for analyzing thermal data woth the purpose of detecting outer-race defects in rolling bearings. Specifically, the study considers thermal-based analysis (TBA) using temperature matrices, intensity-based analysis (IBA) using thermal images, and combinations of these two methods. These approaches are evaluated based on their ability to classify the severity of the defects, building on promising results previously obtained in the field of Infrared Breast Thermography. An accuracy and F1-score exceeding 90% were achieved by combining the temperature matrix with the thermal image using pseudo colors and processing them with the VGG deep learning algorithm. These outcomes indicate the potential of IRT in assessing the condition of rolling bearings. It should be noted that while this work has explored the use of IRT for the classification of the health state of rolling bearings by running different operative conditions and taking thermal images from various angles and distances, further experiments are needed to fully validate the effectiveness of this approach.
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13:30-15:30, Paper WeBT3.4 | |
Value-Based Smart Retrofitting of Maintenance in the Hydropower Plants of Celsia (I) |
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Esteves Meneses, Luis Alfredo | Celsia |
Benavides, Ana Maria | Universidad De Los Andes |
Barbieri, Giacomo | Universidad De Los Andes |
Olaya, Camilo | Universidad De Los Andes |
Mantilla, Carlos Alberto | Celsia |
Keywords: Prognostics & health management, Industry 4.0 , Maintenance engineering and management
Abstract: Smart Retrofitting in maintenance indicates the development of maintenance services through the retrofitting of legacy devices with the functionalities of data collection, data communication and data processing. Many companies nowadays desire to retrofit their assets through the implementation of Prognostics and Health Management (PHM) services to assist in better predicting their future state and making timely and sound decisions. In this context, this work presents the PHM center developed by the company Celsia in the Alto Anchicayá hydropower plant and discusses the available approaches for estimating the value brought by PHM investments. Even if different works can be found in the literature with this purpose, only the economic feasibility of PHM implementations is generally considered. Whereas, in value-based decision-making different dimensions are embraced and not only the performance and cost ones. Therefore, the need of a value model to support decision-making concerning PHM implementations is presented and the potential of System Dynamics for this purpose is discussed.
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13:30-15:30, Paper WeBT3.5 | |
Systematic Review of Difference between Topology Optimization and Generative Design |
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Srivastava, Jagriti | Kyoto University of Advanced Science |
Kawakami, Hiroshi | Kyoto University of Advanced Science |
Keywords: Additive manufacturing, Industry 4.0 , Smart manufacturing
Abstract: This paper aims to study the concept and highlight the methodical difference between the results acquired by design for additive manufacturing methodologies: Topology Optimization (TO) and Generative Design. By meeting particular requirements and reducing a specified cost function, topology optimization (TO) is a mathematical technique that spatially optimizes the distribution of material inside a particular domain which is frequently mistaken for generative design. Software providers claim that generative design is more holistic because it is based on part requirements and restrictions and considers the design, manufacturing process, function, and many other crucial factors. TO as a classical approach has been around for over three decades and due to additive manufacturing, interest in TO is re-established. whereas generative design is an innovative approach that has recently gained acceptance through Computer-Aided Design (CAD) software. The bracket engine problem from General Electric is used as a case study to show how the TO and generative design approaches differ. Examples from earlier literature are taken into account for TO, and Autodesk Fusion 360 (educational license) software is used to produce the outputs for generative design. After carefully examining the entire procedure and the outcomes, a comparison chart is added to highlight the key distinctions between the two approaches.
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13:30-15:30, Paper WeBT3.6 | |
Real-Time Vision Sensor for Volumetric Flowrate Estimation in Robotic Fused Filament Fabrication |
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Badarinath, Rakshith | The Pennsylvania State University |
K Raju, Basil | Digital University Kerala |
Anshad K, Mohammed | Digital University |
Prabhu, Vittaldas | Penn State |
Susan Thomas, Sinnu | Digital University Kerala |
Keywords: Additive manufacturing, Process supervision, Smart manufacturing systems
Abstract: Fused Filament Fabrication (FFF) is one of the most widely used additive manufacturing processes where a part is built layer by layer of deposited polymer material extruded from a heated nozzle. The real-time sensing and control of the FFF process could improve the robustness of the process and the quality of the fabricated part. One of the critical process variables in FFF is the output polymer flow rate, which can be estimated by measuring the thermoplastic material extruded in real-time. Using computer vision, a live video feed of the polymer deposition process can be used as an input for in-situ extrusion width measurements. This paper explores various image processing workflows to improve the measurement latencies of a previously developed vision-based extrusion width measurement approach. The new image processing workflow helps improve the measurement rate by 6x compared to the original workflow, thereby offering prospects of realizing real-time feedback control for FFF.
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13:30-15:30, Paper WeBT3.7 | |
IWAAM: An Automated System for Monitoring and Control of Wire-Arc Additive Manufacturing |
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Coutinho, Fernando | Federal Univ. of Rio De Janeiro |
Lizarralde, Nicolas | Federal University of Rio De Janeiro |
Mendes, Marcel | Federal University of Rio Janeiro |
Ferreira Bostrom, Rodrigo | Federal University of Rio De Janeiro |
Henriques da Silva, Thales | Federal University of Rio De Janeiro |
de Oliveira Couto, Marcus Vinícius | Federal University of Rio De Janeiro |
Lizarralde, Fernando | Federal Univ. of Rio De Janeiro |
Keywords: Additive manufacturing, Advanced manufacturing
Abstract: In this work, a wire-arc additive manufacturing (WAAM) automated system named iWAAM is presented. iWAAM is an automated system for monitoring and control of WAAM depositions. The communication framework is based on ROS (Robot Operating System) and kuka experimental package which allow the execution of predefined trajectories (ros control ) or online trajectory correction during the deposition. The power source control and configuration, and the deposition sequence are also embedded in the proposed framework. A Graphical User Interface (GUI), based on Qt, is used to monitor process variables, such as arc current, voltage, wire feed speed and travel speed. Furthermore, iWAAM controls the fabrication process of parts designed by external planners or by simple depositions using primitive trajectories (raster, zigzag, circular). In addition, a web interface is presented, allowing the users to monitor the process remotely. Experimental results of actual WAAM depositions illustrate the functionalities of the proposed automated system.
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13:30-15:30, Paper WeBT3.8 | |
Visualization of Key Performance Indicators in the Production System in the Context of Industry 4.0 (I) |
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García, Carlos Andrés | Universidad De Las Fuerzas Armadas ESPE |
Caiza, Gustavo | Universidad PolitÉcnica Salesiana |
Guizado, Diego Alexis | Universidad Técnica De Ambato |
Naranjo, Jose Ezequiel | UTA |
Ayala Baño, Elizabeth Paulina | Universidad Técnica De Ambato |
Ortiz, Alexandra | Universidad Tecnica De Ambato |
Garcia, Marcelo Vladimir | Basque Country University |
Keywords: Enterprise integration, Protocols and information communication, Decentralized and distributed control
Abstract: Industry 4.0 has revolutionized the methods to automate and analyze a process, as is the case of implementing Key Performance Indicators (KPIs) that reflect the correct functioning of a working task. Besides, the use of the Internet of Things (IoT), Cyber-Physical Systems (CPS), and other technologies in Industry 4.0 provide an enormous amount of data. For these reasons, this article presents the design of a methodology that contains stages of process analysis, design, implementation, and validation to obtain an interface that shows key production indicators in a simple and friendly way. The cloud platform receives the information from the machine using OPC and MQTT protocols implemented in a low-cost hardware device without changing the current automation hardware platform.
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13:30-15:30, Paper WeBT3.9 | |
A Hybrid Deep Learning-Based Approach for Rolling Bearing Fault Prognostics (I) |
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Neto, Domicio | University of Coimbra |
Petrella, Lorena | University of Coimbra |
Henriques, Jorge | Univ of Coimbra |
Gil, Paulo | FCT - the New University of Lisbon |
Cardoso, Alberto | University of Coimbra |
Keywords: Maintenance engineering and management, Intelligent maintenance systems, Intelligent system techniques and applications
Abstract: Predictive Maintenance (PdM) has the potential to revolutionize the industry by providing advanced techniques to assess the condition of an industrial system and yield key information that can help optimize maintenance planning and prevent unexpected faults and breakdowns. Nevertheless, PdM is far from being universally applied and it is still the subject of increasing research. Thus, developing new approaches has great relevance to help PdM become a practical reality for the industry. PdM can also bring benefits in terms of sustainability, by reducing human and material resources waste, which is one of the main objectives of Circular Manufacturing initiatives. In this context, rolling bearings are one of the most studied components, as most industrial systems with rotating mechanisms contain bearings, which are prone to a number of faults caused by natural and unnatural wear. In this work, an hybrid Deep Learning (DL) approach is proposed, combining a Convolutional Neural Network (CNN) with a Gated Recurrent Unit (GRU) network to predict Remaining Useful Life (RUL) using rolling bearing vibration data preprocessed with the Short-Time Fourier Transform (STFT). This model was trained and validated using the PRONOSTIA public dataset, which is a popular benchmark for rolling bearing prognostics. The obtained results are satisfactory, providing RUL estimates close to the true values in most test cases, proving the competitiveness of the approach and its potential.
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13:30-15:30, Paper WeBT3.10 | |
In-Situ Proces Control Strategies for Selective Laser Melting |
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Al-Saadi, Taha Mubarak | University of Sheffield |
Rossiter, J. Anthony | Univ of Sheffield |
Panoutsos, George | University of Sheffield |
Keywords: Additive manufacturing, Fuzzy control systems, Applications in advanced materials manufacturing
Abstract: Selective Laser Melting (SLM) is an additive manufacturing process that has been attracting the attention of researchers and developers in academia and industry over the last two decades. The SLM manufacturing process is capable of producing sophisticated industrial tools and geometrically complex parts in fewer steps (near net-shape), thus saving resources compared to subtractive manufacturing processes. However, the current industry-scale platforms for manufacturing metal parts via SLM do not sufficiently exploit online feedback control strategies. There is still significant potential for advanced process control which can enhance the overall performance of the system, as well as enable sophisticated manufacture, for example via active control of microstructure to enhance part performance in geometrically complex parts. This paper presents a comparison between the performance of three well-known industrial control strategies, to illustrate strengths and weaknesses in addition to addressing the key challenges and identifying some research opportunities in the field.
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13:30-15:30, Paper WeBT3.11 | |
ML²-Enabled Condition-Based Demand, Production, Inventory, and Maintenance Planning (I) |
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Wesendrup, Kevin | University of Muenster |
Hellingrath, Bernd | University of Muenster |
Keywords: Prognostics & health management, Production planning and control, Intelligent manufacturing systems
Abstract: Production planning and control is pivotal to meeting customer demand and maximizing profit. At the same time, machine breakdowns compromise these goals, which can be tackled with a good maintenance strategy. Here, advances in condition-based maintenance and prognostics and health management allow predicting the health state of production machines through sensor data and prescribing optimal demand, production, inventory, and maintenance plans. Here, machine learning (ML) is promising for accurate health predictions using sensor data and decision-making in complex, highly dynamic production environments. Thus, in this work, two ML algorithms are applied. First, a data-driven regression algorithm predicts the health of a machine. This forecast is forwarded to a reinforcement learning algorithm (i.e. proximal policy optimization, recently made famous by its application within ChatGPT) to optimize demand, production, inventory, and maintenance plans. A computational study shows excellent performances of the ML-based health prediction and planning algorithms, which surpass traditional maintenance strategies.
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13:30-15:30, Paper WeBT3.12 | |
Spatio-Temporal LPV Model of 2D Workpiece Temperature for Direct Laser Deposition |
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da Fonseca Pereira, Guilherme | University of Kassel |
Jelicic, Goran | University of Kassel |
Kroll, Andreas | University of Kassel |
Keywords: Additive manufacturing, LPV system identification
Abstract: Additive manufacturing of metallic components presents challenges regarding quality assurance and consistency, owing to the workpiece’s complex spatially-dependent temperature history and a lack of suitable models for closed-loop temperature control of the fabrication process. The selected case study is the laying of cladding material (workpiece) through Direct Laser Deposition. The paper proposes identifying a linear spatio-temporal parameter-varying model for the workpiece temperature for control-oriented applications. For this, the temperature distribution is reconstructed from data measured by an infrared camera. The model structure is derived from the inhomogeneous heat equation. Finally, the model parameters are identified using a nonlinear least-squares solver. The relationships between theoretical and estimated model parameters are presented.
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13:30-15:30, Paper WeBT3.13 | |
Maintenance Management Practices Using Digital Twins Framework: Oil Extraction Pumping System Case Study (I) |
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Salgado Duarte, Yorlandys | AGH University of Science and Technology |
Szpytko, Janusz | AGH University of Science and Technology |
Keywords: Intelligent maintenance systems, Maintenance engineering and management, Maintenance models and services
Abstract: Conceptually, the digital twins' framework is a virtual representation of an object, system, or process. However, one of its significant contributions has been to merge certain features into a single framework: updating the system modeled from real-time data, using simulation, machine learning, and reasoning to aid decision-making. Specifically, in the maintenance management field and its associated decision-making, the contributions have been prominent, and in this paper, we intend to contribute in the same direction. Here, we describe an adaptive digital twin model designed to coordinate maintenance activities in an oil extraction pumping system. The model is a digital representation of the maintenance decision-making process and cognitive management. The adaptability comes from a self-calibration of the distributed operating parameters of the modeled system under study using a machine learning approach with smart layers in the data management filtering and synthesis. Given the nature of a maintenance modeling process, where randomness and planning are merged, the Monte Carlo method emerges as an easy way to convolute the stochastic degradation due to the system operation and the planning of maintenance activities to keep it working with the required standards. This paper discusses the conceptual model implementation for an oil extraction pumping system using the digital twins' framework and proposes the first exposure of the modeling results in practice as a study case. The modeling results justify the improvements introduced by implementing the digital twins' framework.
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13:30-15:30, Paper WeBT3.14 | |
Health Condition Assessment of MV XLPE and Bare Cables. Case Study (I) |
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Rosero Zuñiga, Laura Sofia | Universidad Nacional De Colombia/Politecnico De Milano |
Cardenas, Luis Alejandro | University |
Garzon, Camilo | University |
Teran, Daniel | University |
Nova Rodriguez, David | University |
Herrera, Fernando | University |
Diaz, Jennifer | Company |
Valbuena, Ivan | Company |
Garcia, Rodolfo | Company |
Keywords: Maintenance engineering and management
Abstract: This paper proposes different models for the evaluation of medium voltage cables through a health condition analysis. For this purpose, several health indexes based on literature are evaluated in each model in order to provide a representation of the health condition of different types of cables. Finally, the available empirical data is used in the proposed models for MV cables from ENEL COLOMBIA S.A ESP.
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WeC01 |
Main Hall |
Advances in Control, Communication, and Optimization for Smart Charging and
Vehicle-To-Everything (V2X) |
Open Invited Session |
Chair: Li, Yang | Chalmers University of Technology |
Co-Chair: Lee, Chih Feng | Polestar Performance AB |
Organizer: Li, Yang | Chalmers University of Technology |
Organizer: Lee, Chih Feng | Polestar Performance AB |
Organizer: Liberati, Francesco | Sapienza University of Rome |
Organizer: Kumtepeli, Volkan | University of Oxford |
Organizer: Quevedo, Daniel | Queensland University of Technology (QUT) |
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16:00-16:20, Paper WeC01.1 | |
Vehicle-To-Grid Optimization Considering Battery Aging (I) |
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Lee, Chih Feng | Polestar Performance AB |
Bjurek, Kalle | Polestar Performance AB |
Hagman, Victor | Chalmers University of Technology |
Li, Yang | Chalmers University of Technology |
Zou, Changfu | Chalmers University of Technology |
Keywords: Electric and solar vehicles, Energy control in transportation
Abstract: Electric vehicles (EVs) play a substantial role in reducing greenhouse gas emission and support a sustainable future. However, the increase of EV may lead to rising electricity demand and fluctuation. In this paper, the EV is proposed as a means to support the electricity grid via the vehicle-to-grid (V2G) technology. To reduce energy demand peaks, charging is planned during off-peak hours. Additionally, the EV battery may be used as a buffer to store energy during off-peak hours, and to supply energy to the grid during peak hours. Furthermore, grid frequency may be regulated by controlling the charging power. Since battery utilization will be increased during V2G operations, battery degradation is included in this study. A case study of Swedish households shows that the V2G is not only contributing to the stability of the grid, but may also help reducing the operating cost of an EV owner, even when battery degradation is considered.
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16:20-16:40, Paper WeC01.2 | |
Computationally Efficient Approach for Preheating of Battery Electric Vehicles before Fast Charging in Cold Climates (I) |
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Hamednia, Ahad | Volvo Car Corporation |
Forsman, Jimmy | Volvo Car Corporation |
Murgovski, Nikolce | Chalmers University of Technology |
Larsson, Viktor | Volvo Car Corporation |
Fredriksson, Jonas | Chalmers University of Technology |
Keywords: Nonlinear and optimal automotive control, Electric and solar vehicles, Modeling, supervision, control and diagnosis of automotive systems
Abstract: This paper investigates battery preheating before fast charging, for a battery electric vehicle (BEV) driving in a cold climate. To prevent the battery from performance degradation at low temperatures, a thermal management system has been considered, including a high-voltage coolant heater (HVCH) for the battery and cabin compartment heating. Accordingly, an optimal control problem (OCP) has been formulated in the form of a nonlinear program (NLP), aiming at minimizing the total energy consumption of the battery. The main focus here is to develop a computationally efficient approach, mimicking the optimal preheating behavior without a noticeable increase in the total energy consumption. The proposed algorithm is simple enough to be implemented in a low-level electronic control unit of the vehicle, by eliminating the need for solving the full NLP in the cost of only 1Wh increase in the total energy consumption.
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16:40-17:00, Paper WeC01.3 | |
Optimization-Free Fast Charging for Lithium-Ion Batteries Using Model Inversion Techniques (I) |
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Li, Yang | Chalmers University of Technology |
Wik, Torsten | Chalmers Univ of Technology |
Huang, Yicun | Chalmers University of Technology |
Zou, Changfu | Chalmers University of Technology |
Keywords: Energy control in transportation, Design, control and monitoring of autonomous transportation systems, Control and scheduling of air transportation
Abstract: We propose a novel fast-charging control framework for lithium-ion (Li-ion) batteries that can leverage a class of models including the high-dimensional, electrochemical-thermal pseudo-two-dimensional model. The control objective is to find the highest battery current while fulfilling various operating constraints. Conventionally, computationally demanding optimization is needed to solve such a constrained optimal control problem when an electrochemical-thermal model is used, leading to practical difficulties in achieving low-cost implementation. Instead, this paper provides an optimization-free solution to Li-ion battery fast charging by converting the constrained optimal control problem into an output tracking problem with multiple tracking references. The required control input, i.e., the charging current, is derived by inverting the battery model. As a result, a nonlinear inversion-based control algorithm is obtained for Li-ion battery fast charging. Results from comparative studies show that the proposed controller can achieve performance close to nonlinear model predictive control but at significantly reduced computational costs and parameter tuning efforts.
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17:00-17:20, Paper WeC01.4 | |
Joint Mobility and Vehicle-To-Grid Coordination in Rebalancing Shared Mobility-On-Demand Systems (I) |
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Zeng, Teng | UC Berkeley |
Moura, Scott | UC Berkeley |
Zhou, Zhe | Shanghai University |
Keywords: Scheduling and optimization of transportation systems, Planning and management of public transportation, Energy control in transportation
Abstract: Vehicle-to-Grid (V2G) technology enables plug-in electric vehicles (PEVs) to act as controllable loads and distributed energy resources for power systems. However, these resources, under the context of Mobility-on-Demand (MoD) market, have yet to be fully exploited for the grid services. This paper investigates how providing energy service from the shared PEVs affects both the power and transportation systems. We consider a shared MoD platform where PEVs can choose to provide either the V2G service or the traveling service when they are rebalanced to future high demand areas. In this market, the power and transportation system operators determine appropriate rewards to attract the PEV drivers. On the other hand, these drivers choose between energy and mobility services to maximize their aggregate benefits. In particular, we analytically model drivers’ preferences for discharging and traveling services through carefully selected utility functions. Moreover, a distributed algorithm is developed to manage the interactions between PEVs and the grid operation. We show that PEV drivers can be encouraged to achieve a desired energy and mobility pattern by optimizing their individual utility. Numerical results demonstrate that integrating energy service into the ride-sourcing market can benefit both PEV drivers and the power system.
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17:20-17:40, Paper WeC01.5 | |
Conflict-Free Charging and Real-Time Control for an Electric Bus Network |
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Lacombe, Remi | Chalmers University of Technology |
Murgovski, Nikolce | Chalmers University of Technology |
Gros, Sebastien | NTNU |
Kulcsar, Balazs | Chalmers University of Technology |
Keywords: Planning and management of public transportation, Scheduling and optimization of transportation systems, Electric and solar vehicles
Abstract: The rapid adoption of electric buses by transit agencies around the world is leading to new challenges in the planning and operation of bus networks. In particular, the limited driving range of electric vehicles imposes operational constraints such as the need to charge buses during service. Research on this topic has mostly focused on the strategic and tactical planning aspects until now, and very little work has been done on the real-time operational aspect. To remedy this, we propose integrating the charging scheduling problem with a real-time speed control strategy in this paper. The control problem is formulated as a mixed-integer linear program and solved to optimality with the branch-and-bound method. Simulations are carried out by repeatedly solving the control problem in a receding horizon fashion over a full day of operation. The results show that the proposed controller manages to anticipate and avoid potential conflicts where the charging demand exceeds the charger capacity. This feature makes the controller achieve lower operational costs, both in terms of service regularity and energy consumption, compared to a standard first-come, first-served charging scheme.
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17:40-18:00, Paper WeC01.6 | |
Multi-Objective Optimization of Operation of Power-Traffic Systems Considering Dynamic Wireless Charging |
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Zhou, Ze | Zhejiang University |
Liu, Zhitao | Zhejiang University |
Su, Hongye | Zhejiang University |
Zhang, Liyan | Wuhan University of Technology |
Wang, Wenhai | Zhejiang University |
Keywords: Scheduling and optimization of transportation systems, Modelling and control of road traffic networks, Energy control in transportation
Abstract: To reduce the consumption of fossil fuels, improve the environment, and optimize the energy structure, electric vehicles (EVs) have been developed rapidly. At the same time, to alleviate the range anxiety of EV users, the corresponding dynamic wireless charging (DWC) technology has also attracted extensive attention. Driven by EVs and DWC, the interdependency between the power system and transportation system becomes tighter. To improve the operation of the power-traffic system, we propose a multi-objective optimization problem incorporating transportation system congestion, power system generation cost, and total EV user charging cost. Assuming that the energy provided by the DWC can meet the consumption in EV travel, we construct a power demand model for grid buses. Furthermore, we model the microscopic characteristics of vehicle behaviors and propose an adaptive route recommendation algorithm. To solve the multi-objective problem, we adopt a non-dominated sorting genetic algorithm II. Finally, the case studies demonstrate the feasibility of the proposed multi-objective optimization problem and the effectiveness and superiority of the proposed algorithm.
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WeC02 |
Room 301 |
Hybrid and Switched Systems Modeling |
Regular Session |
Chair: Medvedev, Alexander | Uppsala University |
Co-Chair: Lee, Jong Min | Seoul National University |
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16:00-16:20, Paper WeC02.1 | |
Design of the Impulsive Goodwin's Oscillator in 1-Cycle |
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Medvedev, Alexander | Uppsala University |
Proskurnikov, Anton V. | Politecnico Di Torino |
Zhusubaliyev, Zhanybai | South West State University |
Keywords: Hybrid and switched systems modeling, Event-based control, Control in system biology
Abstract: This paper presents a systematic approach to design a hybrid oscillator that admits an orbitally stable periodic solution of a certain type with pre-defined parameters. The parsimonious structure of the Impulsive Goodwin's oscillator (IGO) is selected for the implementation due to its well-researched rich nonlinear dynamics. The IGO is a feedback interconnection of a positive third-order continuous-time LTI system and a nonlinear frequency and amplitude impulsive modulator. A design algorithm based on solving a bilinear matrix inequality is proposed yielding the slope values of the modulation functions that guarantee stability of the fixed point defining the designed periodic solution. Further, assuming Hill function parameterizaton of the pulse-modulated feedback, the parameters of those rendering the desired stationary properties are calculated. The character of perturbed solutions in vicinity of the fixed point is controlled through localization of the multipliers. The proposed design approach is illustrated by a numerical example. Bifurcation analysis of the resulting oscillator is performed to explore the nonlinear phenomena in vicinity of the designed dynamics.
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16:20-16:40, Paper WeC02.2 | |
Parametric Piecewise-Affine Approximation of Nonlinear Systems: A Cut-Based Approach |
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Gharavi, Leila | Delft University of Technology |
De Schutter, Bart | Delft University of Technology |
Baldi, Simone | Southeast University |
Keywords: Hybrid and switched systems modeling
Abstract: Piecewise-affine (PWA) approximations are widely used among hybrid modeling frameworks as a way to increase computational efficiency in nonlinear control and optimization problems. A variety of approaches to construct PWA approximations have been proposed, most of which are tailored to specific application areas by using some prior knowledge of the system in their assumptions and/or steps. In this paper, a parametric method is proposed to identify PWA approximations of nonlinear systems, without any prior knowledge of their dynamics or application requirements. The algorithm defines the regions parametrically using hyperplanes to cut the domain, and increases the number of regions iteratively until a user-defined error tolerance criterion is met. General remarks are given on the algorithm’s implementation and a case study is provided to illustrate its application to vehicle dynamics.
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16:40-17:00, Paper WeC02.3 | |
Stochastic Hybrid Model Predictive Control: Application to Parallel Hybrid Electric Vehicles |
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Park, Hyun Min | Seoul National University |
Jung, Hyein | Seoul National University |
Oh, Tae Hoon | Kyoto University |
Oh, Se-Kyu | Hyundai Motor Company |
Lee, Jong Min | Seoul National University |
Keywords: Model predictive control of hybrid systems, Stochastic control, Hybrid and alternative drive vehicles
Abstract: Hybrid electric vehicles (HEVs) are attracting attention for their high fuel efficiency and low emissions compared to diesel-powered vehicles. The fuel efficiency of the HEV is highly dependent on the optimal power split ratio. The problem of finding the optimal power split ratio trajectory is difficult to solve with linear and/or deterministic controllers because it has nonlinear and stochastic characteristics. In this study, stochastic hybrid model predictive control (SHMPC) was applied to the HEV system. Piecewise affine (PWA) modeling of HEV systems was performed to model nonlinear systems with smaller model-plant mismatch compared to linear models. Furthermore, to account for the driver's stochastic behavior, a scenario-based stochastic model predictive control (SMPC) approach was employed. Controllers of scenario-based linear SMPC and scenario-based SHMPC are built. The controllers were tested in MATLAB / Simulink HEVP2 Reference Application simulation environment.
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17:00-17:20, Paper WeC02.4 | |
Koopman Representation for Boolean Networks |
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Qi, Hongsheng | Chinese Academy of Sciences |
Valcher, Maria Elena | Universita' Di Padova |
Shi, Guodong | The Australian National University/The University of Sydney |
Keywords: Hybrid and switched systems modeling, Discrete event modeling and simulation, Control over networks
Abstract: Boolean networks, as logical dynamical systems whose system states are Boolean variables, arise from applications in biology, computer networks, and social networks etc. The representation and control of Boolean networks have attracted a lot of attention in recent years. On a parallel line of research, Koopman developed an operator view of nonlinear dynamical systems in early 1930s, which shows that using observable functions all nonlinear dynamics can be represented as (infinite dimensional) linear systems. In this paper, we present a framework for representing Boolean networks via Koopman approach. First of all, we construct addition and scalar multiplication operations over the set of logical functions over the binary field, defining a linear Boolean function space. Then associated with any Boolean mapping, the induced Koopman operator is defined as an operator over such Boolean function space. Next, we show that if there exists a set of logical functions that are invariant in the Koopman sense, a Boolean network can be represented by a finite-dimensional linear system. This Koopman perspective for Boolean networks is also extended to controlled Boolean networks.
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17:20-17:40, Paper WeC02.5 | |
Feedback Shaping for Boolean Networks |
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Qi, Hongsheng | Chinese Academy of Sciences |
Valcher, Maria Elena | Universita' Di Padova |
Shi, Guodong | The Australian National University/The University of Sydney |
Keywords: Hybrid and switched systems modeling, Discrete event modeling and simulation, Control over networks
Abstract: Boolean networks, as logical dynamical systems where the system states are Boolean variables, arise from applications in biology, computer networks, and social networks etc. In this paper, we present a framework to evaluate whether and how the closed-loop dynamics of a controlled Boolean network can be shaped into any prescribed form by state-feedback control. We refer to this problem as to the feedback shaping for Boolean networks. First of all, based on the linear representation of Boolean networks, we establish a necessary and sufficient rank condition for a controlled Boolean network to be feedback shapable or not. Next, we design an algorithm for the synthesis of closed-loop dynamics for a feedback shapable Boolean network, such that for any given controlled Boolean network and a desired closed-loop dynamics, one can always find a feedback control law so that the closed-loop dynamics is precisely realized.
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17:40-18:00, Paper WeC02.6 | |
Inner and Outer Homeomorphisms for Mechanical Systems Subject to Non-Smooth Impacts |
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Menini, Laura | University of Rome Tor Vergata |
Possieri, Corrado | Università Degli Studi Di Roma "Tor Vergata" |
Tornambe, Antonio | Univ. Di Roma Tor Vergata |
Keywords: Hybrid and switched systems modeling
Abstract: Inner and outer homeomorphisms are considered for restoring the continuous differentiability (with bounded derivatives) with respect to time of the configuration of a rigid mechanical system subject to inequality constraints at the times of non-smooth impacts. The performances of the approach are tested by simulations.
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WeC03 |
Room 302 |
Marine Robotics: The Breeze of Innovation and Remote Access to the Sea II |
Open Invited Session |
Chair: Bibuli, Marco | CNR-INM |
Co-Chair: Zereik, Enrica | Cnr - Inm |
Organizer: Bibuli, Marco | CNR-INM |
Organizer: Zereik, Enrica | Cnr - Inm |
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16:00-16:20, Paper WeC03.1 | |
Robust Hierarchical Tracking Control of Vehicle-Manipulator Systems (I) |
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Dyrhaug, Jan Inge | Norwegian University of Science and Technology (NTNU) |
Tveter, Erling | Norwegian University of Science and Technology |
Schmidt-Didlaukies, Henrik M. | Norwegian University of Science and Technology |
Basso, Erlend A. | Norwegian University of Science and Technology |
Pettersen, Kristin Y. | Norwegian Univ. of Science and Tech |
Gravdahl, Jan Tommy | Norwegian University of Science and Technology (NTNU) |
Keywords: Autonomous underwater vehicles, Adaptive and robust control in marine system, Autonomous mobile robots
Abstract: For vehicle-manipulator systems (VMSs) to perform precise operations, a robust tracking control framework is required. Moreover, to exploit the platform's redundancy, it is desirable that the framework allows several tasks to be completed simultaneously. In this work, a robust hierarchical tracking controller for floating-base robots is presented. In addition to providing uniform global asymptotic stability (UGAS) in free motion and allowing a total task dimension greater than the number of degrees of freedom (DoFs), the proposed controller includes a sliding mode effect and is proved to achieve UGAS even in the presence of bounded disturbances. Moreover, it is proved that uniform global ultimate boundedness (UGUB) is obtained if a continuous approximation of the sliding mode term is used. The stability results are proved mathematically, and are validated through simulations of an articulated intervention autonomous underwater vehicle (AIAUV).
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16:20-16:40, Paper WeC03.2 | |
Task-Priority Operational Space Control for Vehicle-Manipulator Systems with Modelling Errors (I) |
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Iversflaten, Markus H. | Norwegian University of Science and Technology |
Sæbø, Bjørn Kåre | Norwegian University of Science and Technology (NTNU) |
Basso, Erlend A. | Norwegian University of Science and Technology |
Pettersen, Kristin Y. | Norwegian Univ. of Science and Tech |
Gravdahl, Jan Tommy | Norwegian University of Science and Technology (NTNU) |
Keywords: Autonomous underwater vehicles, Adaptive and robust control in marine system, Nonlinear and optimal marine system control
Abstract: The dynamics of underwater vehicle-manipulator systems (UVMSs) are very hard to model, which reduces the feasibility of model-based control approaches. Even so, such strategies prove useful in redundancy resolution. In this paper, higher-order sliding mode control is combined with task-priority operational space control (OSC) in order to handle and utilize the redundancy of UVMSs despite the presence of dynamic model errors. At each task level, the generalized super-twisting algorithm is implemented to reject effects caused by model errors while maintaining a continuous control signal. The general problem of OSC with uncertain models is analyzed, and some of its challenges are highlighted, including an algebraic loop. We conduct a simulation study on a highly redundant UVMS, where we compare task-level higher-order sliding mode control to proportional-derivative control. Though this paper is motivated by challenges specific to UVMSs, the results also hold for other vehicle-manipulator systems.
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16:40-17:00, Paper WeC03.3 | |
Internal Model Control for AUVs with Output Time Delays and Input Disturbances (I) |
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Pedersen, Simon | Aalborg University |
Liniger, Jesper | Aalborg University |
Sørensen, Fredrik Fogh | Aalborg University |
von Benzon, Malte | Aalborg Universitet |
Eggert Nielsen, Morten | Aalborg University |
Mai, Christian | Aalborg University |
Keywords: Autonomous underwater vehicles, Marine system navigation, guidance and control, Unmanned marine vehicles
Abstract: Autonomous Underwater Vehicles (AUVs) are increasingly being used for offshore inspection tasks. This paper investigates how navigation using Simple Internal Model Control for Proportional-Integral-Derivative Control (SIMC-PID) operates in a realistic offshore environment with waves and ocean current acting as input disturbances while the available underwater sensors introduce time delays on the output signals. First, the time delays are determined by investigating available absolute positioning sensor systems. Then, a model of the AUV and the external disturbances is established. The model-based SIMC-PID controller is tuned and examined based on acceptable disturbance rejection while tolerating the dominant time delays. Two simulation case studies show that the heave controller, in both cases, struggles to stabilize in 0 to 8 meters depths, while the surge and sway controllers tolerate the Doppler Velocity Log case (DVL) acceptably. Short Baseline (SBL) shows unacceptable performance in 0 to 15 meters depth. It is concluded that the simplicity of the SIMC-PID controller is an advantage and, therefore, useful when time delays are relatively small, but more advanced techniques must be applied for larger delays such as those introduced by SBL systems.
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17:00-17:20, Paper WeC03.4 | |
Merging BSP Based Swarm Dynamics and Distributed Ledger Technologies for Smart Marine Infrastructures (I) |
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Bonsignorio, Fabio | University of Zagreb |
Zereik, Enrica | Cnr - Inm |
Keywords: Control architectures in marine systems, Decentralized control and systems, Networks of robots and intelligent sensors
Abstract: Distributed ledger technologies, together with AI, smart systems and robotics could provide a scalable and robust platform for the smart underwater and surface marine infrastructures of the close future. They will be harbours or ports, marine farms or remote tourism facilities - only accessible through robotic avatars - for protected areas or for the elders. Autonomous Marine Vehicles, IoT networks, and humans will coexist in highly heterogeneous multivendor multiplatform environments where market transactions and complex administrative procedures will be ubiquitous. Some blockchains such as the Ethereum network are able to provide distributed scalable computing and trustable functionalities, capable of managing both technical interactions and market transactions among very diversified autonomous agents. For these reasons they seem to provide a valuable backbone for the smart marine infrastructure of the coming decades. In this paper we outline our research and innovation strategy and present our results showing the potential benefits of a subsidiary architecture integrating distributed ledger technologies with swarms of autonomous surface robots implemented by a Belief Space Planning approach.
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17:20-17:40, Paper WeC03.5 | |
Horizon Detection and Tracking in Sea-Ice Conditions Using Machine Vision (I) |
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Sandru, Andrei | Aalto University |
Kujala, Pentti | Aalto University |
Visala, Arto | Aalto University, ELEC School |
Keywords: Autonomous surface vehicles, Sensing, Sensor integration and perception
Abstract: An automated process is proposed for horizon detection and tracking using machine vision cameras and in polar, sea-ice conditions. These conditions present unique challenges for machine vision applications, such as a large amount of clutter (e.g. icebergs) and secondary edge lines from broken ice pieces. The process is divided in two parts: a more computationally expensive, yet robust detection algorithm in the first stage, based on Convolutional Neural Networks, and used to detect the horizon line in an arbitrary sea-ice image; followed by a tracking algorithm, responsible of efficiently detecting the horizon line in the subsequent images of a sequence. We propose two tracking algorithms, one based on the traditional Canny and Hough line detection methods; and a second novel approach using entropy as a measure of randomness, to segment between sea-ice and sky. Our automated process was compared to manually obtained ground-truth data and the results indicate good agreement, especially for the texture-based tracking algorithm.
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17:40-18:00, Paper WeC03.6 | |
Singularity-Free Formation Path Following of Underactuated AUVs (I) |
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Matous, Josef | NTNU (Norwegian University of Science and Technology) |
Pettersen, Kristin Y. | Norwegian Univ. of Science and Tech |
Varagnolo, Damiano | NTNU - Norwegian University of Science and Technology |
Paliotta, Claudio | SINTEF |
Keywords: Autonomous underwater vehicles, Multi-vehicle systems, Navigation, guidance and control
Abstract: This paper proposes a method for formation path following control of a fleet of underactuated autonomous underwater vehicles. The proposed method combines several hierarchic tasks in a null space-based behavioral algorithm to safely guide the vehicles. Compared to the existing literature, the algorithm includes both inter-vehicle and obstacle collision avoidance, and employs a scheme that keeps the vehicles within given operation limits. The algorithm is applied to a six degree-of-freedom model, using rotation matrices to describe the attitude to avoid singularities. Using the results of cascaded systems theory, we prove that the closed-loop system is uniformly semiglobally exponentially stable. We use numerical simulations to validate the results.
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WeC04 |
Room 303 |
Estimation and Observer Design: Theory and Applications |
Open Invited Session |
Chair: Zemouche, Ali | CRAN UMR CNRS 7039, University of Lorraine |
Co-Chair: Chakrabarty, Ankush | Mitsubishi Electric Research Laboratories |
Organizer: Zemouche, Ali | CRAN UMR CNRS 7039, University of Lorraine |
Organizer: Belkhatir, Zehor | University of Southampton |
Organizer: Chakrabarty, Ankush | Mitsubishi Electric Research Laboratories |
Organizer: Rajamani, Rajesh | Univ. of Minnesota |
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16:00-16:20, Paper WeC04.1 | |
A High-Gain Observer Design for Nonlinear System with Delayed Measurements: Application to a Quadrotor UAV (I) |
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Dam, Quang Truc | Université De Rouen |
Thabet, Rihab El Houda | IRSEEM/ESIGELEC |
Ahmed Ali, Sofiane | IBISC Laboratory |
Guerin, Francois | Universite Du Havre |
Abdl Ghani, Hasan | University of Rouen Normandy |
Keywords: Time-delay systems, Delay compensation for linear and nonlinear systems, UAVs
Abstract: The paper deals with design of high-gain Observer for nonlinear system with delayed output measurements and bounded disturbances. The new structure of the proposed observer exhibits good performance in term of allowing a higher MAVTD (Maximum Allowable Value of the Time-Delay) comparing to the existing works, where the MAVTD is limited due to the high value of the high-gain parameter. Based on LMI technique and using Lyapunov-Krasovskii functional, an explicit relation between MAVTD and the LMI tuning parameters is deduced from the stability analysis of the proposed observer. The efficiency of the proposed structure is illustrated through an application to a Quadrotor UAV and a comparison with standard and cascade high-gain observers is performed.
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16:20-16:40, Paper WeC04.2 | |
LMI-Based H∞ Observer Design for Nonlinear Lipschitz System (I) |
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Mohite, Shivaraj | University of Lorraine |
Alma, Marouane | Université De Lorraine, France |
Zemouche, Ali | CRAN UMR CNRS 7039, University of Lorraine |
Haddad, Madjid | SEGULA Technologies |
Keywords: Nonlinear observers and filter design, Observer design
Abstract: The problem of circle criterion-based H∞ observer design for nonlinear systems is addressed in this article. An LMI-based observer is developed for the nonlinear Lipschitz systems with linear outputs under the presence of noise/disturbances. The proposed LMI condition is obtained by using reformulated Lipschitz property, standard Young’s relation and a newly defined positive definite matrix multiplier. The inclusion of the matrix multiplier adds additional numbers of decision variables in the LMI, which provides extra degrees of freedom from a feasibility point of view. Further, the performance of the proposed observer is validated using numerical examples.
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16:40-17:00, Paper WeC04.3 | |
Multi-Pass Extended Kalman Smoother with Partially-Known Constraints for Estimation of Vapor Compression Cycles (I) |
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Deshpande, Vedang M. | Mitsubishi Electric Research Laboratories |
Laughman, Christopher | Mitsubishi Electric Research Laboratories |
Keywords: Nonlinear observers and filter design
Abstract: State and parameter estimation methodologies have the potential to make a significant impact in the development of broad array of capabilities for widely-used vapor compression cycles, including advanced controls, performance monitoring, data-driven modeling, and deployment of digital twin technologies. However, the nonlinearity and numerical stiffness of large physics-based models of these systems pose challenges for the practical implementation of estimators that must also satisfy the physical state constraints. We present a three-pass fixed-interval smoothing method developed in the extended Kalman estimation formalism that incorporates linear inequality and partially-known nonlinear equality constraints defined in terms of unknown parameters of the system. The smoothing method is demonstrated to have high estimation accuracy during joint state and parameter estimation of the cycle model representing a realistic system that is implemented in Julia language leveraging automatic differentiation capabilities.
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17:00-17:20, Paper WeC04.4 | |
A Moving Horizon State and Parameter Estimation Scheme with Guaranteed Robust Convergence (I) |
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Schiller, Julian D. | Leibniz University Hannover |
Muller, Matthias A. | Leibniz University Hannover |
Keywords: Nonlinear observers and filter design, Observer design
Abstract: We propose a moving horizon estimation scheme for joint state and parameter estimation for nonlinear uncertain discrete-time systems. We establish robust exponential convergence of the combined estimation error subject to process disturbances and measurement noise. We employ a joint incremental input/output-to-state stability (δ-IOSS) Lyapunov function to characterize nonlinear detectability for the states and (constant) parameters of the system. Sufficient conditions for the construction of a joint δ-IOSS Lyapunov function are provided for a special class of nonlinear systems using a persistence of excitation condition. The theoretical results are illustrated by a numerical example.
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17:20-17:40, Paper WeC04.5 | |
Enhanced High-Gain Observer for Blood and Micro-Robot Velocity Estimation in Magnetic Drug Targeting (I) |
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Bouhadjra, Dyhia | University of Genoa |
Courtial, Estelle | Université D'Orléans |
Fruchard, Matthieu | University of Orléans |
Zemouche, Ali | CRAN UMR CNRS 7039, University of Lorraine |
Keywords: Nonlinear observers and filter design, Robust estimation, Systems biology
Abstract: Micro-robots have a promising prospect to be used in healthcare and bioengineering applications due to their capability to access hard-to-reach areas, allowing them to overcome the limitations of many conventional clinical methods. Controlling these micro-robots in blood vessels is an essential technology for several applications such as targeted drug delivery. One approach is to use a magnetic resonant navigation control strategy which allows precise manipulation of the micro-robot by adjusting the frequency and intensity of the magnetic field. The accuracy and robustness of this technique rely on the knowledge of some parameters such as blood and micro-robot velocities. In previous control designs, the blood velocity was assumed to be known and its pulse was supposed to be constant. This assumption did not reflect reality and reduced the feasibility of the control system. Considering this fact, this paper addresses the problem of estimating the velocity of the blood and micro-robot using an enhanced high-gain observer. Simulation results are carried out in MATLAB/Simulink to demonstrate the effectiveness of the proposed observer with comparisons to the standard high-gain observer.
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17:40-18:00, Paper WeC04.6 | |
Robust Moving-Horizon Estimation for Quasi-LPV Discrete-Time Systems (I) |
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Arezki, Hasni | Université De Lorraine |
Alessandri, Angelo | Università Di Genova |
Zemouche, Ali | CRAN UMR CNRS 7039, University of Lorraine |
Keywords: Robust estimation, Robustness analysis, Linear parameter-varying systems
Abstract: This paper deals with moving horizon estimation for a class of quasi-LPV systems. Under both observability condition and incremental exponential input output-to-state stability~(i-EIOSS) assumption, novel stability conditions of the moving horizon estimator~(MHE) are proposed. Such conditions guarantee exponential robust stability of the MHE based on a particular prediction step that is independent of the dynamic of the system. An application to vehicle motion estimation, using the kinematic model, is provided to show the validity and effectiveness of the proposed method, and to support the theoretical results.
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WeC05 |
Room 304 |
Port-Hamiltonian Systems in Modeling, Simulation and Control |
Open Invited Session |
Chair: Ramirez, Hector | Universidad Federico Santa Maria |
Co-Chair: Le Gorrec, Yann | FEMTO-ST, ENSMM |
Organizer: Ramirez, Hector | Universidad Tecnica Federico Santa Maria - AC3E FB0008 |
Organizer: Le Gorrec, Yann | FEMTO-ST, ENSMM |
Organizer: Maschke, Bernhard | Univ Claude Bernard of Lyon |
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16:00-16:20, Paper WeC05.1 | |
Finite Dimensional Shape Control Design of Linear Port-Hamiltonian Systems with In-Domain Pointwise Inputs (I) |
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Ponce, Cristobal | Universidad Técnica Federico Santa María |
Ramirez, Hector | Universidad Federico Santa Maria |
Le Gorrec, Yann | FEMTO-ST, ENSMM |
Keywords: Passivity-based control, Port Hamiltonian distributed parameter systems
Abstract: This paper is concerned with shape control of a class of infinite-dimensional port-Hamiltonian system, using an early lumping approach, i.e. the dynamic controller synthesized from a low-order discretized version of the system. The approach provides an optimal criterion for choosing a free parameter of the controller so that the closed-loop system converges to the best approximation of the desired imposed shape. The methodology is based on the so called control by interconnection method and structural invariant from which an analytical expression is obtained for the shapes that the system can actually achieve. An Euler-Bernoulli beam model with pointwise inputs is used as example to illustrate the proposed methodology.
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16:20-16:40, Paper WeC05.2 | |
Structure Preserving Discontinuous Galerkin Approximation of One-Dimensional Port-Hamiltonian Systems (I) |
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Thoma, Tobias | Technical University of Munich |
Kotyczka, Paul | Technical University of Munich |
Keywords: Port Hamiltonian distributed parameter systems, Infinite-dimensional systems (linear case), Structural properties
Abstract: In this article, we present the structure preserving discretization of linear one-dimensional port-Hamiltonian (PH) systems of two conservation laws using discontinuous Galerkin (DG) methods. We recall the DG discretization procedure which is based on a subdivision of the computational domain, an elementwise weak formulation with up to two integrations by parts, and the interconnection of the elements using different numerical fluxes. We present the interconnection of the element models, which is power preserving in the case of conservative (unstabilized) numerical fluxes, and we set up the resulting global PH state space model. We discuss the properties of the obtained models, including the effect of the flux stabilization parameter on the spectrum. Finally, we show simulations with different parameters for a boundary controlled linear hyperbolic system.
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16:40-17:00, Paper WeC05.3 | |
Implicit Port-Hamiltonian Systems: Structure-Preserving Discretization for the Nonlocal Vibrations in a Viscoelastic Nanorod, and for a Seepage Model (I) |
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Bendimerad-Hohl, Antoine, Amine | ISAE Supaero |
Haine, Ghislain | Institut Superieur De l’Aeronautique Et De L’Espace |
Lefevre, Laurent | Univ. Grenoble Alpes |
Matignon, Denis | ISAE |
Keywords: Port Hamiltonian distributed parameter systems, Infinite-dimensional systems (linear case)
Abstract: A structure-preserving partitioned finite element method (PFEM), for the semi-discretization of infinite-dimensional explicit port-Hamiltonian systems (pHs), is extended to those pHs of implicit type, leading to port-Hamiltonian Differential Algebraic Equations (pH-DAE). Two examples are dealt with: the nonlocal vibrations in a viscoelastic nanorod in 1D, and the dynamics of a fluid filtration model, the Dzektser seepage model in 2D.
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17:00-17:20, Paper WeC05.4 | |
Port Maps of Irreversible Port Hamiltonian Systems (I) |
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Maschke, Bernhard | Univ Claude Bernard of Lyon |
Kirchhoff, Jonas | Technische Universität Ilmenau |
Keywords: Lagrangian and Hamiltonian systems
Abstract: Irreversible Port Hamiltonian Systems are departure of Port Hamiltonian Systems as they are generated not only by a Hamiltonian function but also by an entropy function and defined with respect to a quasi-Poisson bracket which embeds the definition of the irreversible phenomena taking place in the system. However the port map, consisting in the input map and the output map were poorly justified and lacked any physical consistency. In this paper, we suggest a novel definition of the port maps which allows to recover not only the energy balance equation (when the Hamiltonian equals the total energy of the system) but also a entropy balance equation including the irreversible entropy creation at the interface (the port) of the system in addition to the entropy creation term due to internal irreversible phenomena.
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17:20-17:40, Paper WeC05.5 | |
Exponentially Stable Regulation of Mechanical Systems to a Path (I) |
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O'Brien, Thomas | University of Newcastle |
Ferguson, Joel | The University of Newcastle |
Donaire, Alejandro | The University of Newcastle |
Keywords: Lagrangian and Hamiltonian systems, Trajectory tracking and path following, Lyapunov methods
Abstract: In this paper we consider the problem of path following control for fully-actuated mechanical systems using the technique of total energy shaping. To this end, a closed loop potential function is designed which is minimised along the desired path. In addition, the kinetic energy is shaped to ensure that the trajectories of the system converge exponentially to the desired path. The design method is applied to a 2-DOF robotic manipulator and simulations are presented to show the closed-loop performance.
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17:40-18:00, Paper WeC05.6 | |
Damping Assignment of Boundary Controlled Port-Hamiltonian Systems with Unknown Open-Loop Damping (I) |
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Toledo Zucco, Jesus Pablo | ONERA |
dos Reis de Souza, Alex | Onera - the French Aerospace Lab |
Vuillemin, Pierre | Onera - the French Aerospace Lab |
Poussot-Vassal, Charles | Onera |
Keywords: Port Hamiltonian distributed parameter systems, Infinite-dimensional systems (linear case), System identification and adaptive control of distributed parameter systems
Abstract: A damping assignment control law for infinite-dimensional port-Hamiltonian systems in one-dimensional space with actuators and sensors located at the spatial boundaries is proposed with the novelty that the boundary damping is unknown. This allows us to fix a desired decay of energy for the cases in which the system is over-damped, poorly damped, and even with negative damping. We propose an observer composed of an infinite-dimensional model and a finite-dimensional one for the state and parameter estimation. The asymptotic convergence of the observer is shown using LaSalle's invariance principle assuming that the trajectories are precompact. Finally, an observer-based adaptive output feedback controller is proposed for the damping assignment in the closed loop. The passivity of the closed-loop system is guaranteed with respect to the initial Hamiltonian of the system under the assumption that the observer is initialized identically to the current state and close enough to the parameter value. The transmission line is used to exemplify this approach.
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WeC06 |
Room 311 |
Nonlinear System Identification III |
Regular Session |
Chair: Goswami, Debdipta | The Ohio State University |
Co-Chair: Yoshida, Hiroshi | NEC Corporation |
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16:00-16:20, Paper WeC06.1 | |
Error Prediction of a Differential Drive Wheeled Robot with a Swivel Caster Wheel |
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Kittisares, Sarin | Tokyo Institute of Technology |
Yasuda, Shinya | NEC Corporation |
Kumagai, Taichi | NEC Corporation |
Yoshida, Hiroshi | NEC Corporation |
Keywords: Machine learning, Nonlinear system identification, Data-driven control
Abstract: In this study, we propose a method to predict the heading error of a differential drive wheeled robot due to misalignment of a swivel caster wheel. A swivel caster wheel, which is often used for balancing a differential drive robot, produces undesired torque to the robot when it changes direction. An error prediction model will allow a controller to compensate for the behaviors of a caster wheel. Support vector regression (SVR) and artificial neural network (ANN) were selected as our prediction methods due to their capabilities to model nonlinear systems. 966 trials of experiments were conducted to obtain the training and testing data. We were able to predict the heading error with initial caster orientation and speed command as the input variables using SVR with radial basis function kernel and multilayer perceptron with ReLU and tanh as the activation functions. The RMSE of SVR was 2.13°, and the RMSE of ANN with ReLU and tanh were 2.12° and 2.11° respectively. Moreover, we also confirmed the robustness of our model by testing it with testing data at 800 mm/s, which is faster than the maximum speed of 600 mm/s in the training data. The RMSE at 800 mm/s were 8.83° for SVR, and 5.92° and 6.25° for ReLU and tanh, respectively
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16:20-16:40, Paper WeC06.2 | |
Rover Inverse Simulation Using a Segmented Model Approach |
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Shilliday, Stuart | University of Glasgow |
McGookin, Euan William | University of Glasgow |
Thomson, Douglas | School of Engineering, University of Glasgow |
Keywords: Grey box modelling, Mobile robots, Guidance navigation and control
Abstract: Using mathematical models to simulate system responses to inputs has been shown to be an effective tool for system design and optimisation. As well as forward simulations, inverting the simulation process allows an even deeper understanding of the system and the design requirements. Presented in this paper is a method of simulation inversion known as GENISA, applied to the case of an electromechanical wheeled rover. The effect of segmenting the mathematical model used in the inverted simulation is investigated and is shown to be more efficient in terms of computational expense. This, however, comes at the cost of an increased susceptibility to chattering (ie. sustained oscillations).
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16:40-17:00, Paper WeC06.3 | |
Delay Embedded Echo-State Network: A Predictor for Partially Observed Systems |
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Goswami, Debdipta | The Ohio State University |
Keywords: Nonlinear system identification, Machine learning, Neural networks
Abstract: This paper considers the problem of data-driven prediction of partially observed systems using a recurrent neural network. While neural network based dynamic predictors perform well with full-state training data, prediction with partial observation during training phase poses a significant challenge. Here a predictor for partial observations is developed using an echo-state network (ESN) and time delay embedding of the partially observed state. The proposed method is theoretically justified with Taken's embedding theorem and strong observability of a nonlinear system. The efficacy of the proposed method is demonstrated on three systems: two synthetic datasets from chaotic dynamical systems and a set of real-time traffic data.
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17:00-17:20, Paper WeC06.4 | |
Nonlinear Multi-Physical System Identification of a Chemical Stirred Tank |
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Mohammadali Zadeh Fard, Arash | KU Leuven, Mechanical Engineering, Division LMSD |
Kirchner, Matteo | KU Leuven, Mechanical Engineering, Division LMSD |
Blockmans, Bart | KU Leuven, Mechanical Engineering, Division LMSD |
Arts, Wouter | KU Leuven, Chem&Tech, Center for Sustainable Catalysis & Enginee |
Sels, Bert | KU Leuven, Chem&Tech, Center for Sustainable Catalysis & Enginee |
Naets, Frank | KU Leuve |
Keywords: Nonlinear system identification, Process modeling and identification, Kalman Filtering
Abstract: This paper presents a coupled electro-thermo-mechanical lumped parameter model for a chemical stirred tank, considering the device-related thermo-mechanical losses and process-related effects. This separation can help compute the key performance factors for competing processes during the scale-up. As the model has unknown thermo-mechanical parameters, two system identification experiment sets are conducted to determine the friction torque and heat transfer coefficient. A low-budget data acquisition system is developed in this study based on the Teensy 4.1 microcontroller to stream the logged data of the installed sensors on the serial port. An extended Kalman filter and a moving horizon estimation exploit the model and measurements to estimate the unknown model parameters. The results include the coupled electro-thermo-mechanical effects in estimating the heat transfer coefficient.
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17:20-17:40, Paper WeC06.5 | |
Comparison of Data-Driven Modeling and Identification Approaches for a Self-Balancing Vehicle |
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Homburger, Hannes | HTWG Konstanz University of Applied Sciences |
Wirtensohn, Stefan | University of Applied Sciences Konstanz |
Diehl, Moritz | University of Freiburg |
Reuter, Johannes | University of Applied Sciences |
Keywords: Nonlinear system identification, Grey box modelling, Machine learning
Abstract: This paper gives a systematic comparison of different state–of–the–art modeling approaches and the corresponding parameter identification processes for a self–balancing vehicle. In detail, a nonlinear grey box model, its extension to consider friction effects, a parametric black box model based on regression neural networks, and a hybrid approach are presented. The parameters of the models are identified by solving a nonlinear least squares problem. The training, validation, and test datasets are collected in full–scale experiments using a self–balancing vehicle. The performance of the different models used for ego–motion prediction are compared in full–scale scenarios, as well. The investigated model architectures can be used to improve both, simulation environments and model–based controller design. This paper shows the upsides and downsides arising from using the different modeling approaches. Videos showing the self–balancing vehicle in action are available at: https://tinyurl.com/mvn8j7vf
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17:40-18:00, Paper WeC06.6 | |
Photovoltaic Arrays' Dynamic Model Parameter Estimation |
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Bobtsov, Alexey | ITMO University |
Mancilla-David, Fernando | University of Colorado, Denver |
Aranovskiy, Stanislav | CentraleSupelec - IETR |
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