| |
Last updated on July 4, 2023. This conference program is tentative and subject to change
Technical Program for Thursday July 13, 2023
|
ThPL |
Main Hall |
Multi-Agent Dynamical Systems: Misaligned Objectives, Equilibria, Learning,
and Asymptotics |
Plenary Session |
Chair: Cho, Dong-il Dan | Seoul National Univ |
|
08:30-09:30, Paper ThPL.1 | |
Multi-Agent Dynamical Systems: Misaligned Objectives, Equilibria, Learning, and Asymptotics |
|
Basar, Tamer | Univ. of Illinois Urbana-Champaign |
Keywords: Multi-agent systems
Abstract: Decision making in dynamic uncertain environments with multiple agents having possibly misaligned objectives arises in many disciplines and application domains, including control (particularly, networked control, such as control and operation of multiple robots, unmanned vehicles, mobile sensor networks, and the smart grid), communications (particularly in transmission of information to multiple destinations under privacy constraints), distributed optimization (particularly, with topological and informational constraints), social networks (such as problems of consensus and dissensus), and economics. A natural framework, and a comprehensive one, for modeling, optimization, and analysis in such systems is that provided by stochastic dynamic games, which accommodates different solution concepts depending on how the interactions among the agents are modeled, such as whether there is a hierarchy among them, or they all operate symmetrically as far as the decision-making process goes. and whether they are fully cooperating or fully non-cooperating, or a mix of the two, as well as whether the mode of cooperation (or non-cooperation) during the evolution of the game dynamics is not fixed and changes depending on external as well as internal factors (driven by events that may be generated partially by the strategies adopted by the agents operating under asymmetric, decentralized information). The inherent asymmetry in information across the agents, with them not operating under the same (and consistent) modeling assumptions, and with strategic interactions taking place in neighborhoods and propagating across the network create major challenges in the decision-making process, necessitating each agent to operate in a non-stationary environment and develop beliefs on others, with the belief generation process leading to what is known as second-guessing phenomenon. Another challenge presents itself in scalability of the decision process, as the size of the population of the agents grows. This latter challenge actually turns out to be a blessing in itself, under some (realistic) structural specifications, as in the high population setting the agents become infinitesimal entities, making the underlying dynamic game asymptotically belonging to the class of mean field games (MFGs), a topic that has attracted intense research activity in recent years. This plenary talk will provide an overview of recent developments in the landscape described above, focusing on some foundational results for both model-based and model-free settings, with the latter involving data-driven policy design, requiring reinforcement learning, zero-order stochastic optimization, and finite-sample analysis. Both single and multiple population scenarios will be covered. Discussion of selected applications and future challenges will conclude the talk.
|
|
ThA04 |
Room 303 |
Wind Turbine and Wind Farm Control: Control Challenges and Solutions I |
Open Invited Session |
Chair: van Wingerden, Jan-Willem | Delft University of Technology |
Co-Chair: Mulders, Sebastiaan P. | Delft University of Technology |
Organizer: van Wingerden, Jan-Willem | Delft University of Technology |
Organizer: Mulders, Sebastiaan P. | Delft University of Technology |
Organizer: Fleming, Paul | NREL |
Organizer: Schlipf, David | University of Stuttgart |
Organizer: Johnson, Kathryn | Colorado School of Mines |
Organizer: Pao, Lucy Y. | University of Colorado Boulder |
|
10:00-10:20, Paper ThA04.1 | |
A Novel Control Architecture for Floating Wind Turbines (I) |
|
Hegazy, Amr | TU Delft |
Naaijen, Peter | Delft University of Technology |
van Wingerden, Jan-Willem | Delft University of Technology |
Keywords: Control system design
Abstract: The control of Floating Wind Turbines (FWTs) is challenging, as they possess much lower natural frequencies related to the structure's rigid body motion, which creates an undesirable coupling between tower motion and the blade pitch control. As a result, the tower motion is negatively damped triggering instability. This is because of the presence of Right Half Plane Zeros (RHPZs) imposing fundamental limitation on the control bandwidth. To address this problem, different solutions were proposed with varying control structures ranging from Single-Input, Single-Output (SISO) controllers to Multiple-input, Multiple-output (MIMO) ones. In this paper, a new control structure, of Single-Input, Multiple-Output (SIMO) is proposed that is able to lift the bandwidth limitation, while using simple elements that match the industry demands.
|
|
10:20-10:40, Paper ThA04.2 | |
Heteroscedastic Bayesian Optimisation for Active Power Control of Wind Farms (I) |
|
Hoang, Kiet Tuan | Norwegian University of Science and Technology |
Boersma, Sjoerd | Wageningen University |
Mesbah, Ali | University of California, Berkeley |
Imsland, Lars | Norwegian University of Science and Technology |
Keywords: Model predictive and optimization-based control, Machine learning and data analytics in process control, Intelligent control of power systems
Abstract: Active power control of wind farms remains an open challenge due to inherent noise in wind power that arises from uncertain wind speed measurements and plant/model mismatch. To leverage the heteroscedastic nature of the wind power noise, heteroscedastic Bayesian optimisation (BO) is used for active power control of wind farms. BO utilises closed-loop performance data to tune the parameters of a stochastic model predictive controller (SMPC) in a systematic and data-efficient manner. This, in turn, allows for enhancing the closed-loop performance of the controller intended to decrease the power tracking error. A case study with 9 turbines in a 3x3 wind farm shows that the heteroscedastic BO approach achieves a reduced closed-loop power tracking error in terms of root-mean-square by 8.89% compared to one that relies on nominal BO and a decrease by 64.99% compared to a nominal model predictive controller (MPC) whose performance is not tuned using closed-loop data and BO.
|
|
10:40-11:00, Paper ThA04.3 | |
Optimal Control for Wind Turbine Wake Mixing on Floating Platforms (I) |
|
van den Broek, Maarten Jan | Delft University of Technology |
van den Berg, Daniel | Delft University of Technology |
Sanderse, Benjamin | CWI |
van Wingerden, Jan-Willem | Delft University of Technology |
Keywords: Control of renewable energy resources, Control system design, Modeling and simulation of power systems
Abstract: Dynamic induction control is a wind farm flow control strategy that utilises wind turbine thrust variations to accelerate breakdown of the aerodynamic wake and improve downstream turbine performance. However, when floating wind turbines are considered, additional dynamics and challenges appear that make optimal control difficult. In this work, we propose an adjoint optimisation framework for non-linear economic model-predictive control, which utilises a novel coupling of an existing aerodynamic wake model to floating platform hydrodynamics. Analysis of the frequency response for the coupled model shows that it is possible to achieve wind turbine thrust variations without inducing large motion of the rotor. Using economic model-predictive control, we find dynamic induction results that lead to an improvement of 7% over static induction control, where the dynamic controller stimulates wake breakdown with only small variations in rotor displacement. This novel model formulation provides a starting point for the adaptation of dynamic wind farm flow control strategies for floating wind turbines.
|
|
11:00-11:20, Paper ThA04.4 | |
UKF-Based Wind Estimation and Sub-Optimal Turbine Control under Waked Conditions (I) |
|
Gonzalez Silva, Jean | Delft University of Technology |
Liu, Yichao | Delft University of Technology |
Ferrari, Riccardo M.G. | Delft University of Technology |
van Wingerden, Jan-Willem | Delft University of Technology |
Keywords: Control of renewable energy resources, Control system design, Dynamic interaction of power plants
Abstract: The knowledge of the Effective wind speed (EWS) allows the designing of wind turbine controllers that regulate power production and reduce loads on turbine components. Traditional single-point measurements are known to suffer from high noise and poor correlation with the EWS. As an alternative to overcome these problems, EWS estimators can be designed. The main challenge is the high non-linearity of the wind speed influence on the drive-train dynamics. Therefore, an estimator based on the unscented Kalman filter (UKF) is proposed and compared against an extended Kalman filter (EKF) and the immersion and invariance (I&I) technique. Simulation results are provided and show the superior performances attained by the UKF. Furthermore, the usefulness of the estimated EWS is demonstrated by designing a sliding mode controller (SMC) that can track a desired power reference. In addition, the controller allows operating in sub-optimal conditions, where load reduction is attained at the expense of power maximization. The proposed estimator’s and controller’s performances are evaluated under wind farm wake conditions via high-fidelity simulations. The findings show that UKF can outperform the EKF and the controller can reduce loads, except under highly waked conditions.
|
|
11:20-11:40, Paper ThA04.5 | |
Control of a DFIG Based Wind Turbine Using Modified Conditional Servo-Compensator (I) |
|
Nguyen, Van Cuong | LSS - Supélec |
Netto, Mariana | Université Gustave Eiffel |
Damm, Gilney | University Gustave Eiffel |
Keywords: Control of renewable energy resources, Application of power electronics, Control system design
Abstract: This paper presents the control of a wind turbine composed by a doubly fed induction generator (DFIG), which provides power to the main grid through a feeder. The control algorithm is designed following the modified Conditional Servo-Compensator (mCS) theory. This control technique was recently developed to a broad class of nonlinear systems, and this paper brings the first result applied to wind turbines. The mCS theory has several advantages compared to others, as it is a robust nonlinear control scheme. First, it provides rigorous stability analysis, that allows explicit definition of performance and operating conditions. Secondly, it is a robust controller, and only needs lump values and bounds for parameters and dynamics. Finally it is very simple and easy to implement, and does not need heavy computer burden, it is only based on standard local measurements, and represents a promising solution for real applications. The theoretical results are verified by simulations using detailed Simpower models. These simulations show very good results facing a Low Voltage Ride Through scenario, which is one of the most severe tests used for practical applications. The proposed scheme could easily be adapted to the control of other applications based on power converters. For example, the control of the interconnection of a full wind farm to the main grid, or the control of a terminal in a DC grid.
|
|
11:40-12:00, Paper ThA04.6 | |
Periodic LQG Wind Turbine Control with Adaptive Load Reduction (I) |
|
Thiele, Frederik | Technische Universität Dresden |
Wisbacher, Sabine | University of Applied Sciences Munich |
Diaconescu, Sabin-Mihai | University Politehnica of Bucharest |
Ossmann, Daniel | Munich University of Applied Sciences HM |
Pfifer, Harald | Technische Universität Dresden |
Keywords: Optimal operation and control of power systems, Control of renewable energy resources, Control system design
Abstract: A periodic linear quadratic Gaussian (LQG) control law augmented with a reference point adaption to enable adequate rotor speed tracking and sufficient load reductions for a wind turbine is presented. The solution of the periodic LQG control problem is based on solving two periodic Ricatti differential equations in continuous time with a multiple shooting integration technique. For this, the available gridded linear time-variant description of the turbine is converted to a harmonic representation using harmonic Fourier approximation. While the periodic LQG controller provides rotor speed tracking and effective damping of the aeroelastic blade modes, the reference point adaption explicitly reduces the loads resulting from the periodic operation of the turbine rotor at the rotor rotational frequency. The performance of the proposed control system is compared against a baseline controller in realistic wind scenarios using a high fidelity nonlinear simulator. The results show a significant damage equivalent load reduction while maintaining adequate rotor speed tracking.
|
|
ThA05 |
Room 304 |
Predictive Control I |
Regular Session |
Chair: Findeisen, Rolf | TU Darmstadt |
Co-Chair: Liu, Steven | University of Kaiserslautern Landau |
|
10:00-10:20, Paper ThA05.1 | |
Distributionally Robust Model Predictive Control for Wind Farms |
|
Liu, Steven | University of Kaiserslautern |
Mark, Christoph | University of Kaiserslautern |
Keywords: Predictive control, Constrained control, Stochastic control
Abstract: In this paper, we develop a distributionally robust model predictive control framework for the control of wind farms with the goal of power tracking and mechanical stress reduction of the individual wind turbines. We introduce an ARMA model to predict the turbulent wind speed, where we merely assume that the residuals are sub-Gaussian noise with statistics contained in an moment-based ambiguity set. We employ a recently developed distributionally model predictive control scheme to ensure constraint satisfaction and recursive feasibility of the control algorithm. The effectiveness of the approach is demonstrated on a practical example of five wind turbines in a row.
|
|
10:20-10:40, Paper ThA05.2 | |
A Model Predictive Control Strategy for Adaptive Railway Bridges |
|
Dakova, Spasena | University of Stuttgart |
Zeller, Amelie | University of Stuttgart |
Reksowardojo, Arka P. | École Polytechnique Fédérale De Lausanne |
Senatore, Gennaro | École Polytechnique Fédérale De Lausanne |
Böhm, Michael | University of Stuttgart |
Blandini, Lucio | University of Stuttgart |
Sawodny, Oliver | Univ of Stuttgart |
Keywords: Predictive control, System analysis and optimization, Modeling
Abstract: The life expectancy of bridges depends mainly on the number and amplitude of load cycles it experiences. This paper presents an optimal control approach for minimizing the magnitude of train induced vibrations of adaptive bridge structures. The control strategy comprises two parts. First, the a coordinate transformation is carried out for each time step at the equilibrium point to exclude the static displacement resulting from the train weight. Second, a model predictive controller (MPC) with state dependent input constraints is designed, that increases the damping of the structure and thus minimizes its vibration amplitudes by employing limited actuator forces. The presented control approach is tested by means of a simulation study. Results show that a 50% increase in damping was achieved through structural adaptation, which could significantly extend the life expectancy of bridge structures.
|
|
10:40-11:00, Paper ThA05.3 | |
A Review of Parameterised MPC Algorithms |
|
Rossiter, J. Anthony | Univ of Sheffield |
Sarbini, Mohammad Adi Mukmin | University of Sheffield |
Keywords: Predictive control, Model predictive and optimization-based control, Particle filtering/Monte Carlo methods
Abstract: This paper provides an evaluation and comparison of popular parameterised model predictive control approaches that have been proposed in the literature in recent years. Using the Generalised Predictive Control (GPC) algorithm as the baseline algorithm, the paper sets out a number of performance criteria to compare and contrast with several other MPC approaches. Numerical examples use 100 random samples of 2, 3, and 4-state models and the approaches are compared using the selected performance criteria.
|
|
11:00-11:20, Paper ThA05.4 | |
Rigid-Tube Nonlinear Model Predictive Control for Path Following |
|
Zieger, Tim | IAV, Otto Von Guericke University Magdeburg, Germany |
Holzmann, Philipp | Technical University of Darmstadt |
Bethge, Johanna | Otto-Von-Guericke University Magdeburg |
Oehlschlägel, Thimo | IAV GmbH |
Findeisen, Rolf | TU Darmstadt |
Keywords: Predictive control, Control problems under conflict and/or uncertainties, Trajectory tracking and path following
Abstract: While rigid-tube model predictive control introduces robustness with respect to bounded uncertainty, its application to reference tracking may result in poor control performance due to improper reference-trajectory design or disturbances. To circumvent this, the combination of path-following and rigid-tube model predictive control is proposed for systems that require merely a geometric transition without an additional time specification. Therefore, we present results on how to combine rigid-tube model predictive control and path-following. Furthermore, we show for a nonlinear system that the proposed control method steers the system, subject to disturbances, to a robust positive invariant set around the path, while repeated feasibility, stability, and convergence can be guaranteed under mild assumptions. Moreover, the effectiveness and gained flexibility of the predictive controller in handling disturbances is demonstrated in a simulation example considering an autonomous mobile robot.
|
|
11:20-11:40, Paper ThA05.5 | |
Tube-Based Coalitional MPC with Plug-And-Play Features |
|
Masero, Eva | University of Seville |
Baldivieso Monasterios, Pablo | The University of Sheffield |
Maestre, Jose M. | University of Seville |
Trodden, Paul | University of Sheffield |
Camacho, Eduardo F. | University of Seville |
Keywords: Predictive control, Robust control (linear case), Time-varying systems
Abstract: This paper presents a distributed setting of model predictive control (MPC) to manage linear multi-agent systems consisting of coupled subsystems. Specifically, local controllers can work in coalitions to improve performance and handle plug-and-play events. This study provides insight into a coalitional MPC strategy based on optimized tubes that handles plug-in and plug-out subsystems. Moreover, we explore an inherent robustness gap to absorb disturbances not covered by the tubes without having to group local controllers. A comparison of our approach with centralized and decentralized MPC is reported using an illustrative example.
|
|
11:40-12:00, Paper ThA05.6 | |
Population-Dynamics-Assisted Coalitional Model Predictive Control for Parabolic-Trough Solar Plants |
|
Sánchez-Amores, Ana | University of Seville |
Martinez-Piazuelo, Juan | Universitat Politecnica De Catalunya |
Maestre, Jose M. | University of Seville |
Ocampo-Martinez, Carlos | Universitat Politecnica De Catalunya (UPC) |
Camacho, Eduardo F. | University of Seville |
Quijano, Nicanor | Universidad De Los Andes |
Keywords: Predictive control, Decentralized control, Game theories
Abstract: This paper proposes a coalitional model predictive control method for temperature regulation in parabolic-trough solar fields. The global optimization problem is divided into a set of local subproblems that will be solved in parallel by a set of coalitions. However, these local (smaller) problems remain coupled by a common global resource constraint. In this regard, we present a population-dynamics-assisted resource allocation approach to fully decouple the local optimization problems. By doing this, each coalition can address its corresponding optimization problem without relying on the solutions of the other coalitions. To illustrate the proposed methodology, we provide simulation results for a 100-loop parabolic-trough solar collector field.
|
|
ThA06 |
Room 311 |
Intelligent Data-Driven Fault Diagnosis, Prognostics and Health Aware
Control |
Open Invited Session |
Chair: Mazzoleni, Mirko | University of Bergamo |
Co-Chair: Jha, Mayank Shekhar | University of Lorraine |
Organizer: Mazzoleni, Mirko | University of Bergamo |
Organizer: Simani, Silvio | University of Ferrara |
Organizer: Jha, Mayank Shekhar | University of Lorraine |
Organizer: Noom, Jacques | Delft University of Technology |
Organizer: Schulte, Horst | HTW Berlin |
Organizer: Verhaegen, Michel | Delft University of Technology |
Organizer: Theilliol, Didier | University of Lorraine |
|
10:00-10:20, Paper ThA06.1 | |
FRAN-X: An Improved Diagnostic Transfer Learning Approach with Application to Ball Bearings Fault Diagnosis (I) |
|
Pitturelli, Leandro | University of Bergamo |
Mazzoleni, Mirko | University of Bergamo |
Rillosi, Luca | University of Bergamo |
Previdi, Fabio | Universita' Degli Studi Di Bergamo |
Keywords: Fault detection and diagnosis, Machine learning
Abstract: Data-driven diagnostic methods are attractive from an industrial and practical perspective due to their limited amount of required prior knowledge about the process or component under monitoring. However, these methods usually require a large amount of healthy and possibly faulty labeled data. Often, gathering and manually labeling a vast dataset is not feasible in real scenarios. Transfer learning has emerged as an answer to the labeling problem, exploiting the idea that the diagnostic knowledge could be reused across multiple different, but related, machines and operating conditions. In this work, we introduce several improvements to the Feature Representation and Alignment Network (FRAN) architecture described in (Chen et al., 2020) devised with the diagnostic transfer learning purpose. Our approach, named FRAN-X, presents improved transfer and diagnostics performance between identical machines in different operating conditions, and it is computationally lighter than its original counterpart. The FRANX approach is evaluated on the CWRU-bearing dataset and on experimental data collected from a Computerized Numerical Control (CNC) workcenter machine.
|
|
10:20-10:40, Paper ThA06.2 | |
Data-Driven Fault Diagnosis under Sparseness Assumption for LTI Systems (I) |
|
Noom, Jacques | Delft University of Technology |
Soloviev, O | Flexible Optical BV |
Verhaegen, Michel | Delft University of Technology |
Keywords: Fault detection and diagnosis, Identification for control
Abstract: Model-based fault diagnosis for dynamical systems is a sophisticated task due to model inaccuracies, measurement noise and many possible fault scenarios. By presenting faults in terms of a dictionary, the latter obstacle is recently addressed using well-known techniques for recovering sparse information (e.g. lasso). However, current state-of-the-art methods still require accurate models and measurements for adequate diagnosis. In our contribution we address the problem of data-driven fault diagnosis in the sense that the model of the linear time-invariant (LTI) system is unknown in addition to the fault. Moreover, our aim is to diagnose (concurrent) faults while only having input/output data and the fault dictionary. This implies the user simply plugs in the data and specifies the set of possible faults in order to know the active faults together with an estimate of the dynamic model. The problem is formulated within a blind system identification context resulting in computationally efficient solutions based on convex optimization.
|
|
10:40-11:00, Paper ThA06.3 | |
A State-Space Approach for Remaining Useful Life Control (I) |
|
Spinola Félix, Mônica | CNRS, GIPSA-Lab, Université Grenoble Alpes, Grenoble INP |
Martinez Molina, John J. | Univ. Grenoble Alpes, GIPSA-Lab |
Berenguer, Christophe | Univ. Grenoble Alpes, CNRS, Grenoble INP |
Keywords: Fault detection and diagnosis, Estimation and filtering, Kalman Filtering
Abstract: This paper presents a state-space approach for controlling the Remaining Useful Life (RUL) of deteriorating systems. The proposed approach supposes the availability of a deterioration model that links the deterioration rate with some manipulable control inputs. Such a link can be a non-linear monotonic function between the deterioration-rate and the manipulable control inputs. We propose a method for designing both state observer and state feedback controller for RUL prediction and control. We consider that the manipulable inputs are affected by additive random disturbances and possible multiplicative unknown parameters. In addition, we assume that the control decisions can not be applied instantaneously on the system, which is modeled as a time-delay between control decisions and manipulable inputs of the deterioration dynamics. The proposed methodology is illustrated on a simulated study case which considers an exponential degradation model.
|
|
11:00-11:20, Paper ThA06.4 | |
Degradation Tolerant Control Learning for Discrete-Time Affine Nonlinear Systems (I) |
|
Kanso, Soha | CRAN CNRS_Université De Lorraine |
Jha, Mayank Shekhar | University of Lorraine |
Theilliol, Didier | University of Lorraine |
Keywords: Learning for control, Consensus and reinforcement learning control, Data-driven control
Abstract: This paper develops a degradation tolerant optimal control in the framework of Reinforcement Learning (RL). Safety-critical and mission-critical systems require the development of new control designs that maintain system stability and performance specifications but also address incipient degradation. The aim of this work is to decelerate the speed of degradation by minimizing a cost function that includes the rate of evolution of degradation and the performance requirements. The controller is developed for discrete-time nonlinear systems affine in control, where the system's states are affected by a nonlinear degradation. Value iteration (VI) algorithm based approach is developed to find suitable approximations of both optimal control policy and optimal cost, while guaranteeing closed-loop stability and minimization of degradation rate. Offline model-based Adaptive Dynamic Programming (ADP) algorithm is developed and implemented using actor-critic structure which involves training of both actor and critic neural networks (NN). After training the actor NN with the optimal policy, the NN is implemented in real time to generate the input of the system. Simulation example shows the efficiency and feasibility of the algorithm.
|
|
11:20-11:40, Paper ThA06.5 | |
Decision Tree Based Diagnosis for Hybrid Model-Based/data-Driven Fault Detection and Exclusion of a Decentralized Multi-Vehicle Cooperative Localization System (I) |
|
El Mawas, Zaynab | University of Lille |
Cappelle, Cindy | Université De Lille |
El Badaoui El Najjar, Maan | University of Lille |
Keywords: AI methods for FDI, Estimation and fault detection, Observer based and parity space based methods for FDI
Abstract: Cooperative navigation systems are one of the main topics of interest in multi- robot systems emerging nowadays, where the question of safety remains a very critical one preventing the actual integration of the technology. In this article, a multi-sensor multi-vehicle Cooperative Positioning System (CPS) is presented, with a hybrid fault detection method under a decentralized architecture, and that is tolerant to simultaneous sensor faults. In order to detect and isolate faults, a set of fault sensitive residuals are generated based on the divergence of Jensen Shannon (DJS ) between the probability distributions predicted by the encoder based evolution model and the various observations obtained by sensors. Then, in order to detect a fault, a data-driven approach is applied, where the classification of faults is done by a pre-trained detection decision tree (D-DT) and isolation random forest (I-RF). The testing and evaluation of the approach is done on real data acquired by three Turtlebot3 equipped with wheel encoders (for odometry), a gyroscope (for the yaw angle) and a Marvelmind localization system (for the global position), and a ground truth is recorded using optitrack system.
|
|
11:40-12:00, Paper ThA06.6 | |
Condition Monitoring Using Domain-Adversarial Networks with Convolutional Kernel Features |
|
Caceres-Castellanos, Cesar | Leibniz University Hannover |
Fehsenfeld, Moritz | Leibniz University Hannover |
Kortmann, Karl-Philipp | Leibniz University Hannover |
Keywords: Fault detection and diagnosis, Machine learning, Time series modelling
Abstract: The data-based condition monitoring and diagnosis of a mechatronic system can be a challenge due to the amount of labeled data traditional methods require. Moreover, transferring a trained classification model from its source domain to another mechatronic system is a difficult task due to even minor differences between sensors, dimensions, or environmental conditions. Additionally, labeled data may not be available or difficult to obtain in this new target domain. In this paper, a novel approach to time series based domain adaptation is proposed by modifying a Domain-Adversarial Neural Network. Therefore, a MiniRocket transform is combined with an artificial neural network as a composed feature extractor. This model aims to extract domain invariant features from multivariate time series data that can be used for cross-domain condition monitoring of mechatronic systems. The model is tested for belt tension monitoring using data from two belt drives considering two types of excitation. Experimental results for wideband excitation show that the proposed model estimates the tension of the belt with high accuracy in the target domain (unsupervised). For the jerk-limited excitation, accuracy is improved for the target domain in a semi-supervised setting.
|
|
ThA07 |
Room 312 |
System Identification for Manufacturing Control Applications |
Open Invited Session |
Chair: Hofreiter, Milan | Czech Technical University in Prague, Fac. of Mechanical Eng |
Co-Chair: Jharko, Elena | V.A. Trapeznikov Institute of Control Sciences |
Organizer: Bakhtadze, Natalia | V.A. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences |
Organizer: Chernyshov, Kirill | V.A. Trapeznikov Institute of Control Sciences |
Organizer: Jharko, Elena | V.A. Trapeznikov Institute of Control Sciences |
|
10:00-10:20, Paper ThA07.1 | |
Calculation and Analysis of Technical and Economic Indicators of the NPP Power Unit (I) |
|
Jharko, Elena | V.A. Trapeznikov Institute of Control Sciences |
Abdulova, Ekaterina | V.A. Trapeznikov Institute of Control Sciences |
Keywords: Modeling of manufacturing operations, Production activity control, Process supervision
Abstract: Technical and economic indicators (TEI) characterize the efficiency, reliability, and durability of power equipment during its operation. Based on automating the determination of TEI directly during the production of electricity, objective information can be obtained on the efficiency of the flow of technological processes, as well as on the actual state of power equipment. The conditions for optimal operation of power plants are determined in the process of analyzing its technical and economic indicators. Therefore, the analysis of indicators is one of the most important tasks of automated process control systems (APCS) of nuclear power plants, which largely determines the efficiency of the power unit.
|
|
10:20-10:40, Paper ThA07.2 | |
Decentralized Relay Feedback Identification of TITO Systems (I) |
|
Hofreiter, Milan | Czech Technical University in Prague, Fac. of Mechanical Eng |
Keywords: Modeling of manufacturing operations
Abstract: The article focuses on the identification of systems with two inputs and two outputs (TITO systems) where strong cross-couplings exist. The transfer functions of all links of TITO systems are determined from the frequency response points obtained from the time courses of input and output quantities during decentralized relay control. The proposed procedure uses the so-called shifting method, which allows to obtain multiple points of the frequency characteristic from one experiment, thus allowing the estimation of linear models with multiple parameters. In addition, the article proposes a new procedure using the shifting method to obtain the steady state gains of individual transfer functions. The application of this procedure is shown on the instance of a methanol-ethanol distillation column.
|
|
10:40-11:00, Paper ThA07.3 | |
A Generalized Stochastic Approximation for the Recursive System Identification (I) |
|
Chernyshov, Kirill | V.A. Trapeznikov Institute of Control Sciences |
Keywords: Identification and model reduction
Abstract: This paper presents an approach for constructing probabilistic approximation type algorithms used in system identification systems. The proposed approach allows obtaining recursive identification algorithms under fairly mild assumptions about noise and disturbances that distort the system. The obtained algorithm does not require inversion of the Hessian of the identification criterion and is robust to changes in the order of the Hessian. This example demonstrates good convergence properties of the obtained algorithm compared to conventional recursive systems.
|
|
11:00-11:20, Paper ThA07.4 | |
Identification of Order, Parameters and State Estimation Via Projection Onto the Plane of Guarantors (I) |
|
Kopysov, Oleg Yu. | DesCartes Science Center |
Keywords: Identification and model reduction
Abstract: The iterative algorithm of simultaneous identification of order, parameters and estimation of state vector of dynamic objects is proposed. The simulation results show the efficiency of the proposed algorithm for the big level of noise in experimental data.
|
|
11:20-11:40, Paper ThA07.5 | |
Detection of Structural Shifts in Commodity Markets in the Mode of Situation and Digital Monitoring (I) |
|
Avdeeva, Zinaida | V.A. Trapeznikov Institute of Control Sciences of RAS |
Grebenyuk, Elena | Trapeznikov Institute of Control Sciences, RAS |
Kovriga, Svetlana | V.A. Trapeznikov Institute of Control Sciences of the Russian Ac |
Keywords: Integrated monitoring, control and security for critical infrastructure systems, Knowledge discover (data mining), Modelling and decision making in complex systems
Abstract: The paper proposes an algorithm for combined monitoring of prices in commodity markets, including (1) digital monitoring to detect structural shifts in the time series of the observation object, (2) situation monitoring of the external environment of its operation to structure the current situation and generate signals about its changes, (3) control of information exchange and the formation of output aggregated signals. Combined monitoring of information about changes in the environment of the object operation (happened, impending or possible) allows you to improve the quality of detection, reduce the delay and form options for possible changes in the state of the object; and thereby ultimately ensure an increase in the efficiency of solving the target problems of analysis and forecasting controlled object.
|
|
11:40-12:00, Paper ThA07.6 | |
Control Retail Demand with Stochastic Dynamic Pricing: Weight Function Optimization (I) |
|
Kitaeva, Anna | National Research Tomsk State University |
Zhukovskiy, Oleg | Tomsk State University of Control Systems and Radioelectronics |
Cao, Yu | National Research Tomsk State University |
Keywords: Inventory control, Operations research, Supply chain management
Abstract: We consider a single product under a finite time horizon and a heterogeneous compound Poisson customers flow with a rate depending on the stock level and an unknown time-dependent weight function. The rate is controlled by a retail price. In the framework of the diffusion approximation of the stock level process and a linear intensity-of-price dependence, we solve the task of the expected profit maximization with respect to the weight function and lot size. We propose a simple approximation of the optimal weight function and investigate the accuracy of this approximation.
|
|
ThA08 |
Room 313 |
Smart Materials Based Mechatronic Systems and Structures: Control Aspects |
Open Invited Session |
Chair: Rakotondrabe, Micky | University of Toulouse |
Co-Chair: Khadraoui, Sofiane | University of Sharjah |
Organizer: Rakotondrabe, Micky | University of Toulouse |
|
10:00-10:20, Paper ThA08.1 | |
Hybrid Output Regulation of Hysteretic Actuators Based on Single-Crystal Shape Memory Alloy Wires (I) |
|
Mandolino, Michele Arcangelo | Saarland University |
Ferrante, Francesco | Università Degli Studi Di Perugia |
Rizzello, Gianluca | Saarland University |
Keywords: Motion control systems, Smart structures, Mechatronics
Abstract: In this paper, we present a novel hybrid feedback controller for a hysteretic actuator based on smart materials. The system under investigation consists of a single-crystal Shape Memory Alloy wire coupled with a biasing mechanism. Starting from a physics-based hybrid description of the nonlinear actuator behavior, a Throw-Catch hybrid strategy is developed to achieve asymptotic regulation of the system output (i.e., position) based on a combination of global and local control schemes. The control law permits the desired regulation goal to be achieved without the need to measure or estimate the complete system state, by solely relying on the actuator output information. After being described, the controller is validated via simulations.
|
|
10:20-10:40, Paper ThA08.2 | |
Distributed-Parameter Bouc-Wen Modeling and Output Feedback Control of a Piezoactuator for Manipulation Task (I) |
|
Trejo, Sergio | Center for Research in Optics |
Flores, Gerardo | Center for Research in Optics |
Rakotondrabe, Micky | University of Toulouse |
Keywords: Modeling, Smart structures, Motion control systems
Abstract: The Bouc-Wen hysteresis model and an Euler-Bernouilli beam bending theory are extended to distributed parameter model for a piezoelectric actuator (piezo actuator). Then we use the separation principle for its control and two types of observers: a neural network-based observer and a high-gain observer. Simulations with various conditions show that better performances are obtained when using the neural network-based observer.
|
|
10:40-11:00, Paper ThA08.3 | |
Energy Based Control of a Bi-Stable and Underactuated Soft Robotic System Based on Dielectric Elastomer Actuators (I) |
|
Soleti, Giovanni | Saarland University |
Prechtl, Johannes | Saarland University |
Massenio, Paolo Roberto | Polytechnic University of Bari |
Baltes, Matthias | Saarland University |
Rizzello, Gianluca | Saarland University |
Keywords: Motion control systems, Smart structures, Robotics technology
Abstract: In this paper, we propose an energy based control approach for a class of underactuated soft robotic systems. The considered case study consists of an elastic structure driven by soft dielectric elastomer actuators, and is able to achieve large bending displacement thanks to a bi-stable design concept. The bi-stability feature, however, causes the system to exhibit an unstable behavior in open-loop. After providing a port-Hamiltonian description of the soft robotic system, sufficient conditions for the existence of an energy based stabilizing controller are provided. A linear matrix inequality approach is then proposed to practically address the design of the controller gain. The effectiveness of the method is verified by means of simulation studies, conducted on an experimentally validated model of the real-life device.
|
|
11:00-11:20, Paper ThA08.4 | |
Multi-Objective Model-Predictive Control for Dielectric Elastomer Wave Harvesters (I) |
|
Hoffmann, Matthias K. | Saarland University |
Heib, Lennart | Saarland University |
Rizzello, Gianluca | Saarland University |
Moretti, Giacomo | Saarland University |
Flaßkamp, Kathrin | Saarland University |
Keywords: System analysis and optimization, Smart structures, Application of mechatronic principles
Abstract: This contribution deals with multi-objective model-predictive control (MPC) of a wave energy converter (WEC) device concept, which can harvest energy from sea waves using a dielectric elastomer generator (DEG) power take-off system. We aim to maximise the extracted energy through control while minimising the accumulated damage to the DEG. With reference to system operation in stochastic waves, we first generate ground truth solutions by solving an optimal control problem, comparing it to the performance of MPC to determine a prediction horizon that trades off accuracy and efficiency for computation. Fixed weights in the MPC scheme can produce unpredictable costs for variable sea conditions, meaning the average rate of cost accumulation can vary vastly. To steer this cost growth, we propose a heuristic to adapt the algorithm by changing the weighting of the cost functions for fulfilling the long-time goal of accumulating a small enough damage in a fixed time. A simulated case-study is presented in order to evaluate the performance of the proposed MPC framework and the weight-adaptation algorithm. The proposed heuristic proves to be able to limit the amount of accumulated damage while improving the energy yield obtained with a comparable fixed-weight MPC.
|
|
11:20-11:40, Paper ThA08.5 | |
Nonlinear Tracking Differentiator and PD Controller for Piezoelectric Actuators in a Robotic Hand (I) |
|
Khadraoui, Sofiane | University of Sharjah |
Fareh, Raouf | University of Sharjah |
Rakotondrabe, Micky | University of Toulouse |
Keywords: Identification and control methods, Micro and nano mechatronic Systems, Smart structures
Abstract: This article deals with the modeling and control design for piezoelectric actuators of a micro-robotic system. Piezoelectric actuators generally exhibit complex and nonlinear behavior due to their inherent asymmetric hysteresis phenomenon, creep nonlinearity, and oscillatory characteristics. Moreover, these actuators are subject to an external disturbance force caused by the interaction with the manipulated objects. It has been shown in practice that these characteristics have a negative and significant impact on the performance of piezoelectric actuators, which increases the difficulty of their control. The main objective of this paper is to account simultaneously for all undesired and complex characteristics outlined above. To this end, our main idea is to lump the hysteresis and creep phenomena, as well as the disturbing manipulation force together as one total disturbance term. The total disturbance is first estimated in real-time via a nonlinear tracking differentiator, then feedback control law is designed to compensate for the disturbance and achieve a good transient profile. To validate and demonstrate the efficacy of the proposed approach, experiments are conducted, and results obtained are discussed.
|
|
11:40-12:00, Paper ThA08.6 | |
Camber Morphing Mechanisms in Control Aspects: Design and Implementation (I) |
|
Jo, Bruce | Tennessee Technological University |
Majid, Tuba | ETH Zurich |
Keywords: Smart structures, Design methodologies, Mechatronics for mobility systems
Abstract: This paper presents state-of-the-art technologies of camber morphing mechanisms from design and implementation perspectives. Wing morphing technologies aim to make the aircraft more energy or aerodynamically efficient during flight by actively adjusting the wing shape. Still, their mechanism designs and implementation aspects for control are often overlooked from a practical sense in many technical articles. Thus, it is of interest that we thoroughly investigate morphing mechanisms and their nature of design principles and methodologies from the implementation and test flight aspects toward control. This paper categorizes the camber morphing mechanisms from a wide collection of literature on morphing wings and their mechanisms. The defined classifications are based on the mechanism’s design features and synthesis methodology, i.e., by the tools and methods used to solve the design problem. The categories are 1) structure-based, 2) material-based, and 3) hybrid. In summary, this review provides researchers in aircraft design and mechatronics systems with choices of materials, actuators, internal and external structure design for wings, and overarching process and design methodologies.
|
|
ThA09 |
Room 314 |
Co-Creative Cyber Physical System in Smart Manufacturing and Logistics II |
Open Invited Session |
Chair: Nishi, Tatsushi | Okayama University |
Co-Chair: Nonaka, Youichi | Hitachi, Ltd |
Organizer: Kaihara, Toshiya | Kobe University |
Organizer: Nishi, Tatsushi | Okayama University |
Organizer: Nonaka, Youichi | Hitachi, Ltd |
|
10:00-10:20, Paper ThA09.1 | |
Dispatching Rules Selection Mechanism Using Support Vector Machine for Genetic Programming in Job Shop Scheduling (I) |
|
Salama, Shady | Kobe University |
Kaihara, Toshiya | Kobe University |
Fujii, Nobutada | Kobe University |
Kokuryo, Daisuke | Kobe University |
Keywords: Job and activity scheduling, Smart manufacturing systems, Industry 4.0
Abstract: Several scholars have suggested using AI techniques to automatically develop algorithms, which is known as “hyper-heuristics”, to reduce the time and effort required in conventional methods. Although the Genetic Programming (GP) approach is the most popular hyper-heuristic approach used to generate dispatching rules to solve Job Shop Scheduling Problems (JSSPs), high computational requirements remain a major challenge for its wide applicability. Therefore, this paper proposes a mechanism to reduce the computational time needed to evaluate the solution quality of evolved rules. The proposed mechanism utilizes training data collected from the initial generation using a new representation to train a Support Vector Machine (SVM) classifier with a kernel of radial basis function. Then, in subsequent generations, the trained classifier is used to select the most promising (high-quality) rules for fitness assessment and discard low-performance ones. Consequently, only high-quality rules are evaluated, and the computational power that could have been used to evaluate poor rules is preserved. The performance of the proposed mechanism is analyzed using ten job shop instances from the literature, with respect to prediction accuracy and computational time. The results verify the effectiveness of the proposed approach in reducing the computational budget of the GP algorithm for JSSPs while achieving high training and testing accuracy.
|
|
10:20-10:40, Paper ThA09.2 | |
Co-Creation of Production Resources and Processes in Pilot and Learning Factories—a Case Study (I) |
|
Kemény, Zsolt | SZTAKI Institute for Computer Science and Control |
Beregi, Richárd | MTA SZTAKI |
Erdos, Gabor | SZTAKI |
Nacsa, János | SZTAKI Institute for Computer Science and Control |
Keywords: Production planning and control, Flexible and reconfigurable manufacturing systems, Internet-of-Things and sensing enterprise
Abstract: Even though co-creation is mostly considered in the context of product and service development in business-to-consumer relations, the approach can very well be applied when production resources are targeted by collaborative problem solving, and a manufacturer takes the role of the customer. However, exploring partly unknown solutions to partly undefined problems does bear risks, requiring a shielding of live production from potential damages. The paper examines a possible solution to such challenges in the form of pilot factories and learning factories by presenting and discussing the structure and selected use cases of an example facility from the perspective of co-creation and its infrastructural support.
|
|
10:40-11:00, Paper ThA09.3 | |
A Discrete Event Simulation Study of Multi-Objective Sales and Operation Planning: A Case of Ethiopian Automotive Industry (I) |
|
Tesfu, Yigedeb Abay | Kobe University |
Kaihara, Toshiya | Kobe University |
Kokuryo, Daisuke | Kobe University |
Fujii, Nobutada | Kobe University |
Keywords: Production planning and control, Supply chain management , Modeling of manufacturing operations
Abstract: Sales and operation planning is an integrated tactical level panning system that balances demand and supply and determines optimum production amount, inventory level, capacity requirements, financial and customer service level indicators. It plays a major role in supply chain planning in enhancing responsiveness of all internal functions and linking them to customers and suppliers. This research aims at reviewing the subject area in the literature and develop a simulation model as an industrial engineering decision support system for an Ethiopian automotive industry. The industry’s sales and operation planning process was surveyed to identify gaps and develop an enhanced simulation model that can be utilized to understand the system behavior and evaluate performance of manufacturing flexibility and inventory control policies. The simulation analysis result demonstrates that the planning technique, flexibility, safety stock and emergency backup supply policies, customer service level and financial gains of the company can be enhanced significantly. The findings from the simulation analysis and their managerial implication are expected to improve technical capability of Ethiopian automotive industry.
|
|
11:00-11:20, Paper ThA09.4 | |
Toward Data-Driven and Multi-Scale Modeling for Material Flow Simulation: Comparison of Modeling Methods (I) |
|
Nagahara, Satoshi | Hitachi, Ltd |
Kaihara, Toshiya | Kobe University |
Fujii, Nobutada | Kobe University |
Kokuryo, Daisuke | Kobe University |
Keywords: Modeling of manufacturing operations, Production planning and control, Discrete event systems in manufacturing
Abstract: Material flow simulation is a powerful tool to realize efficient operation in complicated production systems such as high-mix and low-volume production. However, it takes significant efforts and expertise to construct accurate simulation models. We have proposed a semi-automatic modeling approach called as data-driven and multi-scale modeling in which various modeling methods are combined to maximize the simulation accuracy for entire production system. In this article, we introduce the overview of the proposed method and experimental results on simple production systems with multiple machines.
|
|
11:20-11:40, Paper ThA09.5 | |
Simulation-Based Optimization Using Virtual Supply Chain Structured by the Configuration Platform (I) |
|
Liu, Ziang | Okayama University |
Shirakashi, Reimon | Okayama University |
Kamiebisu, Ryuichi | Okayama University |
Nishi, Tatsushi | Okayama University |
Matsuda, Michiko | Kanagawa Institute of Technology |
Keywords: Industry 4.0 , Supply chain management , Cyber physical system
Abstract: This study develops a decision support system for optimizing the performance of virtual supply chains. In the proposed framework, an exhaustive search algorithm is developed to search for all the possible solutions. For each candidate solution that is generated by the algorithm, a configuration platform is used to generate a virtual supply chain and evaluate its performance. The performance of the proposed decision support system is examined on a small size supply chain optimization problem. The experimental results show that the proposed algorithm can find the optimal solution for the optimal manufacturer selection and lot size problem.
|
|
11:40-12:00, Paper ThA09.6 | |
Robust Anomaly Map Assisted Multiple Defect Detection with Supervised Classification Techniques |
|
Rožanec, Jože Martin | Jožef Stefan International Postgraduate School |
Zajec, Patrik | Jožef Stefan International Postgraduate School |
Theodoropoulos, Spyros | National Technical University of Athens |
Koehorst, Erik | Philips Consumer Lifestyle BV |
Fortuna, Blaž | Qlector D.o.o |
Mladenić, Dunja | Jožef Stefan Institute |
Keywords: Manufacturing plant control, Smart manufacturing, Intelligent manufacturing systems
Abstract: Industry 4.0 aims to optimize the manufacturing environment by leveraging new technological advances, such as new sensing capabilities and artificial intelligence. The Discriminatively trained Reconstruction Anomaly Embedding Model (DRAEM) technique has shown state-of-the-art performance for unsupervised classification. The ability to create anomaly maps (images highlighting areas where defects probably lie) can be leveraged to provide cues to supervised classification models and enhance their performance. Our research shows that the best performance is achieved when training a defect detection model by providing an image and the corresponding anomaly map as input. Furthermore, such a setting offers consistent performance when framing defect detection as a binary or multiclass classification problem and is unaffected by class balancing policies. We performed the experiments on three datasets with real-world data provided by Philips Consumer Lifestyle BV.
|
|
ThA10 |
Room 315 |
Decision Making and Planning for Transportation |
Regular Session |
Chair: P. Vinod, Abraham | Mitsubishi Electric Research Laboratories |
Co-Chair: Hinostroza, Miguel | Norwegian University of Science and Technology (NTNU) |
|
10:00-10:20, Paper ThA10.1 | |
Decision Making for Automated Driving by Reachability of Parameterized Maneuvers |
|
Di Cairano, Stefano | Mitsubishi Electric Research Laboratory |
Skibik, Terrence | University of Colorado BOulder |
P. Vinod, Abraham | Mitsubishi Electric Research Laboratories |
Weiss, Avishai | University of Michigan |
Berntorp, Karl | Mitsubishi Electric Research Labs |
Keywords: Autonomous vehicles, Mission planning and decision making, Constrained control
Abstract: We consider a decision making system for automated driving that has the objective of determining what maneuvers are feasible for the current vehicle, route, and traffic conditions. For the maneuvers determined to be feasible, a motion planner can then generate the trajectories that achieve the corresponding goals, without the risk of wasting computations in searching for a trajectory of an impossible maneuver. We solve the decision making problem by constructing backward reachable sets for goals and collision areas, based on maneuvers that are generated by dynamical models with decision parameters. Online, we only need to check the existence of parameter values that provide membership of the state-parameter vector in a goal reachable set, and non-membership in all collision reachable sets, which entails simple and fast computations. We evaluate the method in scenarios involving lane change and braking maneuvers.
|
|
10:20-10:40, Paper ThA10.2 | |
A Decision-Making Method for Swarm Agents in Attack-Defense Confrontation |
|
Wang, Lexing | Institute of Automation, Chinese Academy of Sciences |
Qiu, Tenghai | Institute of Automation, Chinese Academy of Sciences |
Pu, Zhiqiang | Institute of Automation, Chinese Academy of Sciences |
Yi, Jianqiang | Institute of Automation, Chinese Academy of Sciences |
Zhu, Jinying | Institute of Automation, Chinese Academy of Sciences |
Zhao, Yanjie | China Academic of Electronics and Information Technology |
Keywords: Mission planning and decision making, Multi-vehicle systems, Coordination of multiple vehicle systems
Abstract: The cooperative decision-making of swarm agents has attracted extensive attention from researchers due to its potential applications in multidisciplinary engineering problems. This paper studies a confrontation problem called asymmetric attack-defense confrontation (i.e., considering the difference in capability and quantity between agents and targets). The objective is to develop an effective self-organized swarm confrontation decision-making method. The decision-making process consists of task allocation decision and swarms motion decision. At each decision-making step, firstly, each agent forms a coalition with other agents autonomously by using a proposed hedonic coalition formation algorithm according to the attribute of targets. Thus, the agents assigned to the same target form a coalition, and swarm agents form several disjoint coalitions. Then, based on the allocated results, the agents are steered toward the corresponding target by a combat stimulus and a proposed selected interaction swarm algorithm. Finally, while the targets are within the agents' attack radius, the agents execute the confrontation decision. Simulation results show the effectiveness of the designed method.
|
|
10:40-11:00, Paper ThA10.3 | |
A Scalable Heuristic for Mission Planning of Mobile Robot Teams |
|
Lager, Anders | ABB AB |
Miloradovic, Branko | Mälardalen University |
Spampinato, Giacomo | Università Degli Studi Di Catania |
Nolte, Thomas | Mälardalen University |
Papadopoulos, Alessandro Vittorio | Mälardalen University |
Keywords: Mission planning and decision making, Mobile robots, Autonomous mobile robots
Abstract: In this work, we investigate a task planning problem for assigning and planning a mobile robot team to jointly perform a kitting application with alternative task locations. To this end, the application is modeled as a Robot Task Scheduling Graph and the planning problem is modeled as a Mixed Integer Linear Program (MILP). We propose a heuristic approach to solve the problem with a practically useful performance in terms of scalability and computation time. The experimental evaluation shows that our heuristic approach is able to find efficient plans, in comparison with both optimal and non-optimal MILP solutions, in a fraction of the planning time.
|
|
11:00-11:20, Paper ThA10.4 | |
Automated Planning for Inspection and Maintenance Operations Using Unmanned Ground Vehicles |
|
Hinostroza, Miguel | Norwegian University of Science and Technology (NTNU) |
Lekkas, Anastasios M. | Norwegian University of Science and Technology |
Transeth, Aksel Andreas | SINTEF Digital |
Luteberget, Bjørnar | SINTEF Digital |
De Jonge, Christian | Equinor, Norway |
Sagatun, Svein Ivar | Equinor, Norway |
Keywords: Mission planning and decision making, Autonomous mobile robots, Trajectory and path planning
Abstract: Offshore oil and gas industry has a strong incentive to improve its traditional operations and move towards more remote controlled and automated installations. This allows for improved efficiency, reduced cost and improved quality, and safety by removing personnel out of harm’s way. The use of Unmanned Ground Vehicles (UGVs) in these upcoming platforms, is relevant for Inspection and Maintenance (I&M) operations. Traditionally, UGVs are used only for pre-defined tasks and have no capabilities for replanning, if a new task is required or any unexpected event occurs. This paper presents a novel concept for I&M operations using automated planning for UGVs. The automated planner is based on a temporal planning algorithm, and considers actions related to, for example, visiting a specific waypoint, inspect a sensor or manipulate an actuator. Also, the proposed system allows to perform replanning in case of any specific location needs to be revisited or a path is blocked. In addition, we couple the mission planner with a UGV guidance, navigation and control system, which has path planning, path following and control capabilities. To assess the performance of the proposed system, an use case for I&M operations on board of an oil and gas platform was simulated and promising results were obtained.
|
|
11:20-11:40, Paper ThA10.5 | |
Real-Time Monitoring and Optimal Vessel Re-Scheduling in Natural Inland Waterways |
|
Nadales, J.M. | Universidad De Sevilla |
Muñoz de la Peña, David | Universidad De Sevilla |
Limon, Daniel | Universidad De Sevilla |
Alamo, Teodoro | Universidad De Sevilla |
Keywords: Maritime transportation planning and control, Scheduling and optimization of transportation systems, Monitoring of transport systems
Abstract: Despite the efforts made by the port community and the academia to develop efficient strategies to mitigate the effect of unexpected events on the planning of vessels through natural waterways, most scheduling algorithms developed so far are not against these events unforseen events. These incidents may lead to nonoptimal operation or even to potentially dangerous situations. To tackle this issue, in this paper we propose a real-time monitoring architecture and a series of optimal rescheduling strategies to re-schedule vessels in real time when an unexpected incident is detected. The objective is to reduce the impact of the incident in the overall process while preserving safety. This is done by detecting deviations from the originally scheduled plans and taking the proper measures when incidents are detected, which will depend on the type of anomaly detected. The proposed methodology is applied to the case of the Guadalquivir river, a natural waterway located in the south of Spain.
|
|
11:40-12:00, Paper ThA10.6 | |
Payload Stabilization for Offshore Cranes: A Unified Controller Based on Flatness |
|
Schubert, Philipp | RWTH Aachen University |
Abel, Dirk | RWTH-Aachen University |
Keywords: Nonlinear and optimal marine system control, Output feedback control, Mechatronics
Abstract: Crane-based handling operations represent a vital part of today's maritime sector. To guarantee both safe and efficient payload handling with ship cranes, payload oscillations induced by the sea swell have to be damped. Approaches for payload stabilization usually consider either vertical position control (Active Heave Compensation, AHC) or sway reduction (Anti Sway Control, ASC). In this paper, a unified control scheme for spatial payload stabilization is proposed, utilizing the differential flatness of the crane system. The presented framework inverts the nonlinear payload dynamics by means of the flat mapping, thus facilitating controller design. Furthermore, the approach provides a systematic way to include the sea disturbance in the controller. Redundancy of the considered knuckle boom crane is exploited to track secondary control objectives. A related cost function weighting the crane's manipulability is derived and used in an optimization-based target selector. The controller design is evaluated in simulation for varying sea disturbances. The results suggest good AHC and ASC capabilities, where the payload's position error is reduced up to 60% for light to medium sea states.
|
|
ThA11 |
Room 411 |
Discrete Event Systems |
Regular Session |
Chair: Giua, Alessandro | University of Cagliari, Italy |
Co-Chair: Lichtenberg, Gerwald | Hamburg University of Applied Sciences |
|
10:00-10:20, Paper ThA11.1 | |
Algebraic Structures in Interpreted Petri Nets |
|
Vazquez, Carlos Renato | Tecnologico De Monterrey |
Ramirez-Trevino, Antonio | CINVESTAV-IPN |
Navarro-Gutiérrez, Manuel | Tecnologico De Monterrey |
Keywords: Petri nets, Discrete event modeling and simulation, Event-based control
Abstract: Modern Discrete Events Systems (SED) such as Manufacturing systems, Transport and Logistic system, among many others, are very large and complex. The bottom-up modeling methodologies based on building basic modules (either in Finite Automata (FA) or Petri nets (PN)) and then merging them using synchronous and permissive products result insufficient (the derived models are large and unreadable). To cope this problem, this paper introduces a modeling methodology based on the novel synchronous product, denotes as ``||". This single product subsumes the previously reported synchronous and permissive products, and it is capable to handle large system in a formal yet efficient way. The main advantage of this new product deals in the fact that it is an associative and commutative operator in the class of Compositional State Machines (CSM). Moreover, (CSM,||) forms a moniod. Furthermore, by defining a partial order relation on the CSM set, a lattice is found. This structure is relevant since the resulting meet operation provides the common subsystems of a couple of systems, and the join operation represents how subsystems build a larger system. Finally, the purpose of this modelling methodology is twofold, on the one hand the model of the system is easy to follow and can be displayed in a Human-Machine Interface (HMI), on the other hand it can be used for analysis and control purposes.
|
|
10:20-10:40, Paper ThA11.2 | |
Verification of Joint Current-State Opacity Using Petri Nets |
|
Zhao, Wenjie | Xidian University |
Giua, Alessandro | University of Cagliari, Italy |
Li, Zhiwu | Xidian University |
Keywords: Discrete event modeling and simulation, Petri nets
Abstract: A discrete event system (DES) is said to be opaque if a predefined secret can never be exposed to an intruder who can observe its evolution. In this paper we consider a problem of joint current-state opacity for a system modeled by a Petri net and monitored by multiple local intruders, each of which can partially observe the behavior of the system. The intruders can synchronously communicate to a coordinator the state estimate they have computed, but not their observations. We demonstrate that the verification of this property can be efficiently addressed by using a compact representation of the reachability graph, called basis reachability graph (BRG), as it avoids the need for exhaustive enumeration of the reachability space. A joint BRG-observer is constructed to analyze joint current-state opacity under such a coordinated decentralized architecture.
|
|
10:40-11:00, Paper ThA11.3 | |
Max-Min-Plus-Scaling Systems in a Discrete-Event Framework with an Application in Urban Railway |
|
van den Boom, Ton J. J. | Delft Univ. of Tech |
De Schutter, Bart | Delft University of Technology |
Gupta, Abhimanyu | Delft University of Technology |
Beek, Ruby | Delft Center for Systems and Control (DCSC), TU Delft |
Keywords: Max-plus algebra, Optimal control of discrete event and hybrid systems, Event-based control
Abstract: In this paper we discuss modelling and control of discrete-event systems using max-min-plus-scaling systems. We analyse how the basic operations max, min, plus, and scaling occur in the modelling phase and we discuss some general forms for the system. Because of the different/deviating character of the signals in a discrete-event MMPS model, we will discuss concepts such as time-invariance and steady-state behavior. In the design of a model predictive controller for MMPS systems we have to revisit the cost functions in light of the discrete-event nature of the signals.We finalize this paper with the an intuitive case study on an urban railway line, performing both modelling and control.
|
|
11:00-11:20, Paper ThA11.4 | |
Formal Verification of Robotic Contact Tasks Via Reachability Analysis |
|
Tang, Chencheng | Technische Universität München |
Althoff, Matthias | Technische Universität München |
Keywords: Reachability analysis, verification and abstraction of hybrid systems, Robots manipulators, Security and safety of HMS
Abstract: Verifying the correct behavior of robots in contact tasks is challenging due to model uncertainties associated with contacts. Standard methods for testing often fall short since all (uncountable many) solutions cannot be obtained. Instead, we propose to formally and efficiently verify robot behaviors in contact tasks using reachability analysis, which enables checking all the reachable states against user-provided specifications. To this end, we extend the state of the art in reachability analysis for hybrid (mixed discrete and continuous) dynamics subject to discrete-time input trajectories. In particular, we present a novel and scalable guard intersection approach to reliably compute the complex behavior caused by contacts. We model robots subject to contacts as hybrid automata in which crucial time delays are included. The usefulness of our approach is demonstrated by verifying safe human-robot interaction in the presence of constrained collisions, which was out of reach for existing methods.
|
|
11:20-11:40, Paper ThA11.5 | |
An Approach to Structured Multilinear Modeling with Relaxed Boolean Output Functions (I) |
|
Engels, Marah | Hamburg University of Applied Sciences |
Lichtenberg, Gerwald | Hamburg University of Applied Sciences |
Knorn, Steffi | TU Berlin |
Keywords: Graph-based methods for networked systems, Grey box modelling
Abstract: A new structured network modeling approach based on binary node indexing and Boolean differentials is introduced. Orthogonal ternary vector lists serve as a structured representation of the model's state dynamics. Tensor decomposition methods are enabled by relaxation to continuous Zhegalkin polynomials due to their inherently multilinear nature. A periodic example is used to demonstrate how a low-dimensional state space can provide a large number of linear independent outputs.
|
|
11:40-12:00, Paper ThA11.6 | |
Neural Network-Based Classification of Oscillation Shapes and Tuning of PID Controllers |
|
Rehan, Ahmed | Khalifa University |
Boiko, Igor | Khalifa University of Science and Technology |
Zweiri, Yahya | Khalifa University |
Keywords: Data-driven control, Nonparametric methods, Learning for control
Abstract: Autotuning is a popular and effective method for tuning the gains of PID controllers. Among various autotuning methods, the Modified Relay Feedback Test (MRFT) stands out as it offers tuning rules that are compatible with a wide range of system characteristics. The tuning rules based on the oscillation shapes are available, however, the classification of the shapes of oscillations is not rigorously dealt with and is still a challenging part of the tuning process. In this study, we propose a solution to this problem by using a Neural Network (NN) to classify the shapes of oscillations. The tuning rules based on these shapes were developed through the MRFT and Optimization Under the Uncertainty principle. Our feed-forward NN classifier can accurately classify four shapes of oscillations in the presence and absence of noise. We compare the results of our NN-based classifier with a Linear Discriminant based classifier and demonstrate superior performance in terms of simplicity and accuracy.
|
|
ThA12 |
Room 412 |
Advanced Control Technologies for Carbon Neutrality and Intelligent
Mobility I |
Invited Session |
Chair: Yasui, Yuji | Honda R&D Co., Ltd. Japan |
Co-Chair: Kako, Junichi | Toyota Motor Corporation |
Organizer: Yasui, Yuji | Honda R&D Co., Ltd. Japan |
Organizer: Kako, Junichi | Toyota Motor Corporation |
Organizer: Nakada, Hayato | Hino Motors, Ltd |
Organizer: Suzuki, Tatsuya | Nagoya Univ |
Organizer: Shen, Tielong | Sophia University |
|
10:00-10:20, Paper ThA12.1 | |
An Occlusion and Interaction-Aware Safe Control Strategy for Autonomous Vehicles (I) |
|
Gangadhar, Siddharth | Carnegie Mellon University |
Wang, Zhuoyuan | Carnegie Mellon University |
Poku, Kofi | Carnegie Mellon University |
Yamada, Naoya | Nagoya University |
Honda, Kohei | Nagoya University |
Nakahira, Yorie | Carnegie Mellon University |
Okuda, Hiroyuki | Nagoya University |
Suzuki, Tatsuya | Nagoya Univ |
Keywords: Autonomous vehicles, Adaptive and robust control of automotive systems, Human and vehicle interaction
Abstract: We consider the problem of safe autonomous driving in the presence of occlusions. Dealing with latent risks arising from occlusions is challenging because there does not exist direct mapping from sensor input to visible threats; attempts to ensure safety for all worst-case latent threats can be infeasible or overly conservative, and accounting for a multitude of latent risks for sufficient future horizon may require prohibitive computation in real-time. To address these issues, in this paper, we propose to use a probability-based predictive controller to make safe decisions for autonomous vehicles. We prove that the proposed safety controller can generate vehicle control profiles that yield the desired safety probability. Numerical and onboard experiments on a visual occluded pedestrian crossing scenario verified the efficacy of the proposed method in real-time. The merits of the proposed control strategy include being able to guarantee long-term safety under occlusions without being over-conservative, handling latent risks caused by on-road interactions in real-time, and ease of design with transparency to the exposed risks.
|
|
10:20-10:40, Paper ThA12.2 | |
Robust Loss Function for Class Imbalanced Semantic Segmentation and Image Classification (I) |
|
Bhat, S Divakar | Honda R&D |
More, Amit | Honda R&D Co., Ltd |
Soni, Mudit | Honda R&D |
Yasui, Yuji | Honda R&D Co., Ltd. Japan |
Keywords: Robot navigation, programming and vision, Neural networks, Autonomous vehicles
Abstract: Real world datasets are often unbalanced. Such an imbalance in data can limit the performance of modern deep learning based solutions by introducing a bias in the trained model. In particular, the trained model show weak performance on sub tasks or classes where the data availability is sparse. In this work, we address such a data imbalance problem and propose a novel modification to the existing cross-entropy loss function to mitigate the issue. Our proposed loss function can amplify the loss gradients generated during the back-propagation step. In particular, we penalize the predictions of the model which can result in higher loss values and gradients. We compare our proposed loss function with several recently proposed approaches and show superior performance. Our experiments show that proposed approach achieves state of the art performance on log-tailed image classification on CIFAR100/10-LT and Imagenet-LT datasets and on semantic segmentation task on Citiscapes dataset.
|
|
10:40-11:00, Paper ThA12.3 | |
Double-Iterative Gaussian Process Regression for Modeling Error Compensation in Autonomous Racing (I) |
|
Su, Shaoshu | University of California, Riverside |
Hao, Ce | University of California, Berkeley |
Weaver, Catherine | University of California Berkeley |
Tang, Chen | UC Berkeley |
Zhan, Wei | University of California, Berkeley |
Tomizuka, Masayoshi | Univ of California, Berkeley |
Keywords: Trajectory tracking and path following, Trajectory and path planning, Learning and adaptation in autonomous vehicles
Abstract: Autonomous racing control is a challenging research problem as vehicles are pushed to their limits of handling to achieve an optimal lap time; therefore, vehicles exhibit highly nonlinear and complex dynamics. Difficult-to-model effects, such as drifting, aerodynamics, chassis weight transfer, and suspension can lead to infeasible and suboptimal trajectories. While offline planning allows optimizing a full reference trajectory for the minimum lap time objective, such modeling discrepancies are particularly detrimental when using offline planning, as planning model errors compound with controller modeling errors. Gaussian Process Regression (GPR) can compensate for modeling errors. However, previous works primarily focus on modeling error in real-time control without consideration for how the model used in offline planning can affect the overall performance. In this work, we propose a double-GPR error compensation algorithm to reduce model uncertainties; specifically, we compensate both the planner's model and controller's model with two respective GPR-based error compensation functions. Furthermore, we design an iterative framework to re-collect error-rich data using the racing control system. We test our method in the high-fidelity racing simulator Gran Turismo Sport (GTS); we find that our iterative, double-GPR compensation functions improve racing performance and iteration stability in comparison to a single compensation function applied merely for real-time control.
|
|
11:00-11:20, Paper ThA12.4 | |
Decision Governor: A Finite State Machine Based Motion Planning Pipeline for Autonomous Driving (I) |
|
Bae, Sangjae | Honda Research Institute, USA |
Isele, David | Honda Research Institute |
Miranda Anon, Alexandre | Honda Research Institute |
Saroya, Manish | Honda Research Institute USA, Inc |
Fujimura, Kikuo | Honda Research Institute USA |
Keywords: Autonomous vehicles, Autonomous mobility, Mission planning and decision making
Abstract: Driving in urban areas requires careful attention for other traffic participants as well as various road structures. Due to the uncertainties inherited from a stochastic decision-making mechanism of unknown participants and unprecedented scene understandings, a motion planning strategy needs to be timely adapted. Therefore, we design a motion planning pipeline that adapts various motion planning strategies based on specific driving situations, examining potential edge cases. We integrate state-of-the-art motion planning strategies associated with various driving intentions. In simulations, we validate the proposed pipeline under diverse driving scenarios, including highway merging, T-junction, four-way intersection, and lane changing in dense traffic scenarios. We also report the on-road demonstration result.
|
|
11:20-11:40, Paper ThA12.5 | |
Design of Reward Function on Reinforcement Learning for Automated Driving (I) |
|
Goto, Takeru | Honda R&D Ltd., Co |
Kizumi, Yuki | Honda Motor Co., Ltd |
Iwasaki, Shun | Honda Motor Co., Ltd |
Keywords: Autonomous vehicles, Learning and adaptation in autonomous vehicles, Trajectory and path planning
Abstract: This paper proposes a design scheme of reward function that constantly evaluates both driving states and actions for applying reinforcement learning to automated driving. In the field of reinforcement learning, reward functions often evaluate whether the goal is achieved by assigning values such as +1 for success and -1 for failure. This type of reward function can potentially obtain a policy that achieves the goal, but the process by which the goal is reached is not evaluated. However, process to reach a destination is important for automated driving, such as keeping velocity, avoiding risk, retaining distance from other cars, keeping comfortable for passengers. Therefore, the reward function designed by the proposed scheme is suited for automated driving by evaluating driving process. The effects of the proposed scheme are demonstrated on simulated circuit driving and highway cruising. Asynchronous Advantage Actor-Critic is used, and models are trained under some situations for generalization. The result shows that appropriate driving positions are obtained, such as traveling on the inside of corners, and rapid deceleration to turn along sharp curves. In highway cruising, the ego vehicle becomes able to change lane in an environment where there are other vehicles with suitable deceleration to avoid catching up to a front vehicle, and acceleration so that a rear vehicle does not catch up to the ego vehicle.
|
|
11:40-12:00, Paper ThA12.6 | |
Deep Adversarial Reinforcement Learning and Its Application to Adaptive Control of a Locomotive Robot (I) |
|
Goto, Nao | Kyoto University |
Kubo, Akihiro | Advanced Telecommunication Research Institute |
Ohashi, Kohei | Kyoto University |
Watanabe, Toshiki | Kyoto University |
Nakanishi, Kosuke | Honda R&D Co |
Yasui, Yuji | Honda R&D Co., Ltd |
Nakamura, Yutaka | RIKEN |
Ishii, Shin | Kyoto University |
Keywords: Autonomous mobile robots, Robot navigation, programming and vision, Learning and adaptation in autonomous vehicles
Abstract: We propose a new deep reinforcement learning (DRL) method in which the RL policy is tuned to be robust against observation noise that would have perturbed their inputs. In particular, the observation noise is produced such to be most harmful for the current controller in a simulated manner. Through benchmark experiment with PyBullet dynamical systems, our new DRL method can improve the robustness of the adaptive controllers in a data-efficient manner. We also show that the method is effective in identifying optimal control of a locomotive robot simulator.
|
|
ThA14 |
Room 414 |
Modern Heuristic Optimization Methods in Smart Grids |
Open Invited Session |
Chair: Majanne, Yrjö | Tampere University |
Co-Chair: Grieu, Stéphane | PROMES-CNRS |
Organizer: Lee, Kwang Y. | Baylor University |
Organizer: Majanne, Yrjö | Tampere University |
|
10:00-10:20, Paper ThA14.1 | |
A Novel Learning-Based MPC with Embedded Profiles Prediction for Microgrid Energy Management |
|
Casagrande, Vittorio | University College London |
Boem, Francesca | University College London |
Keywords: Control of renewable energy resources, Neural networks in process control, Model predictive and optimization-based control
Abstract: This paper presents a novel algorithm for microgrid energy management based on a differentiable learning-based Model Predictive Control (MPC) for jointly optimising profiles prediction and control performance. Specifically, we propose an algorithm for the online training of a Neural Network (NN) that predicts the unknown parameters of the MPC optimisation problem during control operation. Since the training is performed online at each time step the controller adapts to possible changes in the system parameters, while avoiding the offline training phase. Differently to standard methods in the literature, the proposed NN is trained by minimising a performance-based loss, i.e. the total cost of the energy trading with the utility grid. Simulation results show that the proposed approach outperforms the traditional approach minimising an estimation-only MSE loss, both when the model parameters are perfectly known and when they are uncertain.
|
|
10:20-10:40, Paper ThA14.2 | |
Optimal Configuration of Self-Consistent Microgrid System with Hydrogen Energy Storage for Highway Service Area (I) |
|
Shi, Ruifeng | North China Electric Power University |
Tang, Keyi | North China Electric Power University |
Lee, Kwang Y. | Baylor University |
Keywords: Control of renewable energy resources, Modeling and simulation of power systems, Smart grids
Abstract: Targeting on the goal of carbon peaking and carbon neutralization, the transportation sector is facing the pressure of carbon reduction, emission reduction and energy transformation simultaneously. Building a green, flexible, self-consistent and sustainable road transportation energy integration system has become an inevitable trend for the future development in an area without power grid. This paper proposes a self-consistent micro grid system model for wind and solar power with hydrogen energy storage for a highway service area without power grid connection. On this basis, a micro grid optimal configuration model is proposed with the goal of minimizing the comprehensive cost of the micro grid in the service area, under the constraints of the battery, hydrogen energy storage system (ESS), and the power balance of the micro grid system. Particle Swarm Optimization (PSO) algorithm is employed to solve the problem for a case study to verify the effectiveness of the model and the method proposed. Experimental results show that the model proposed in this paper not only improves the renewable energy utilization rate of the system, but also improves the reliability of power supply, verifying the effectiveness of the micro grid configuration scheme for the highway service area containing hydrogen ESS.
|
|
10:40-11:00, Paper ThA14.3 | |
Algorithms Comparison for Hydrogen Storage Predictive Control on an Islanded Microgrid (I) |
|
GauchÉ, Adrien | PowiDian, Nantes Universite, Ecole Centrale Nantes, CNRS, LS2N, |
Morin, David | PowiDian |
Chenouard, Raphaël | Ecole Centrale De Nantes, LS2N, UMR6004, Nantes Université |
Ghanes, Malek | Centrale Nantes |
Keywords: Smart grids, Optimal operation and control of power systems, Modeling and simulation of power systems
Abstract: This paper presents a comparison of some classical metaheuristic (Particle Swarm Optimsation, Simulated Anneling) and deterministic (Branch & Bound, Pattern Search) algorithms for the optimization of the storage control of a microgrid over a whole year with real data. These algorithms are compared on the relevance of the controls in terms of energy autonomy, power losses and wear of the hydrogen chain as well as on the computational burden for a small embedded controller. This allows to highlight a type of algorithm adapted to a limited time and means of calculation that we find in real conditions. This study also points out the importance of prediction errors and their impacts when controlling real systems.
|
|
11:00-11:20, Paper ThA14.4 | |
Production Line Energy Cost Optimization with Renewable Energy Resource Usage in a Flexible Job Shop Configuration (I) |
|
Mota, Bruno | Polytechnic of Porto |
Faria, Pedro | Polytechnic Institute of Porto |
Ramos, Carlos | Polytechnic Institute of Porto |
Keywords: Modeling and simulation of power systems, Smart grids, Intelligent control of power systems
Abstract: Ever-increasing electricity prices due to inflation has become one of the main problems for manufacturing industries to deal with, mainly in a competitive market. The usage of Renewable Energy Resources (RER)s can be a great way to mitigate the energy costs of the electricity market, by not only covering the energy consumption but also turning a profit with the surplus. This paper aims to address these issues by proposing an intelligent production line scheduling system, in a flexible job shop configuration, that focuses on reducing energy costs. It considers dynamic pricing, RERs usage and surplus selling, and complex constraints applied in the production plan. To achieve these results, a Genetic Algorithm (GA) is employed. A case study from the literature, that uses real production data, is presented which does not take into account energy selling. Results show that with the proposed GA energy costs can be further reduced by 24.6% when considering RERs surplus selling.
|
|
11:20-11:40, Paper ThA14.5 | |
Modified Active Disturbance Rejection Control with Pre-Compensation for a Class of High-Order System (I) |
|
Dai, Chengbo | Tsinghua University |
Shi, Gengjin | Tsinghua University |
Liu, Shaojie | Tsinghua University |
Zhang, Yu-Long | Beijing Institute of Technology |
Li, Donghai | Tsinghua University |
Keywords: Optimal operation and control of power systems, Control system design, Power systems stability
Abstract: With more and more sustainable energy integrated into the bulk power system, the coal-fired unit is obliged to speed up the response to the deep peek and frequency regulation command, and this results in great challenges for the control systems. To improve the control performance of the coal-fired unit, a modified active disturbance rejection control with pre-compensation (PMADRC) is proposed for high-order systems with the type of K/(Ts+1)n. The stability, sensitivity, and robustness of the proposed PMADRC are analyzed. An effective tuning procedure is also provided based on plenty of simulations. Besides, contrastive simulations and experiments based on the water tank level control platform validate the superiority of PMADRC in setpoint tracking and disturbance rejection. The advantages of the PMADRC guarantee high control performance and make it have the potential for applications in coal-fired units.
|
|
11:40-12:00, Paper ThA14.6 | |
Predictive Management of Batteries in Networked Microgrids under Planned Islanding |
|
Mannini, Romain | PROMES-CNRS |
Eynard, Julien | University of Perpignan Via Domitia |
Grieu, Stéphane | PROMES-CNRS |
Keywords: Smart grids
Abstract: Microgrids (MGs) and networked microgrids (NMGs) are emerging as an efficient way to increase the penetration of distributed energy resources into the main grid. In this context, the present paper focuses on the predictive management of a bank of batteries and electric vehicle (EV) batteries in NMGs under planned islanding. MGs with standard loads, moderate critical loads, and highly critical loads are considered in this sudy. Different storage configurations and EV scenarios are evaluated. Batteries can be discharged in a normal or in a degraded way, according to three islanding discharging modes, to support MGs with critical loads. Moreover, a reward system, which is used to reward proper (i.e., successful) islanding, is put in place. The proposed predictive strategy has recourse to model-based predictive control (MPC) and is compared to a rule-based reference strategy. The simulation results highlight that the predictive strategy has the ability to decide which MG in the NMG will achieve successful islanding. In addition, such a strategy takes advantage of the EVs the NMG is equipped with to supply highly critical loads, thus enhancing the NMG robustness and energy self-sufficiency.
|
|
ThA15 |
Room 415 |
Machine Learning Methods and Applications |
Regular Session |
Chair: Siang, Lim C. | University of British Columbia |
Co-Chair: Cao, Yankai | University of British Columbia |
|
10:00-10:20, Paper ThA15.1 | |
Data Quality Over Quantity: Pitfalls and Guidelines for Process Analytics |
|
Siang, Lim C. | University of British Columbia |
Elnawawi, Shams | University of British Columbia |
Rippon, Lee | University of British Columbia |
O'Connor, Daniel L. | Control Consulting Inc |
Gopaluni, Bhushan | University of British Columbia |
Keywords: Machine learning and data analytics in process control, Industrial applications of process control, Process modeling and identification
Abstract: A significant portion of the effort involved in advanced process control, process analytics, and machine learning involves acquiring and preparing data. Literature often emphasizes increasingly complex modelling techniques with incremental performance improvements. However, when industrial case studies are published they often lack important details on data acquisition and preparation. Although data pre-processing is unfairly maligned as trivial and technically uninteresting, in practice it has an out-sized influence on the success of real-world artificial intelligence applications. This work describes best practices for acquiring and preparing operating data to pursue data-driven modelling and control opportunities in industrial processes. We present practical considerations for pre-processing industrial time series data to inform the efficient development of reliable soft sensors that provide valuable process insights.
|
|
10:20-10:40, Paper ThA15.2 | |
Interpretable Soft Sensors Using Extremely Randomized Trees and SHAP |
|
Cao, Liang | University of British Columbia |
Ji, Xiaolu | University of British Columbia |
Cao, Yankai | University of British Columbia |
Li, Yupeng | China University of Geosciences |
Siang, Lim C. | University of British Columbia |
Li, Jin | Burnaby Refinery |
Pediredla, Vijay Kumar | University of British Columbia, Vancouver |
Gopaluni, Bhushan | University of British Columbia |
Keywords: Machine learning and data analytics in process control, Process modeling and identification, Industrial applications of process control
Abstract: Tree-based ensemble models are easy to implement and have been widely used in various fields. However, they have limitations in industrial process applications since the majority of tree-based ensemble models are prone to over-fitting. In addition, the internal structure of tree-based ensemble models is very complex and the output of the model is also difficult to explain, which makes its application in industrial soft sensors very challenging. The purpose of this work is to build accurate and interpretable soft sensors for industrial processes. First, to deal with overfitting, a robust tree-based ensemble model, extremely randomized trees, is used to build accurate soft sensors. Then, to improve model interpretability, an interpretable machine learning algorithm, Shapely additive explanation, is used to infer the global and local contributions of each feature to the predictions. Finally, the effectiveness of the proposed algorithms is validated on real industrial fluid catalytic cracker unit data.
|
|
10:40-11:00, Paper ThA15.3 | |
A Modular Framework for Stabilizing Deep Reinforcement Learning Control |
|
Lawrence, Nathan P. | University of British Columbia |
Loewen, Philip D. | Univ. of British Columbia |
Wang, Shuyuan | UBC |
Forbes, Michael Gregory | Honeywell |
Gopaluni, Bhushan | University of British Columbia |
Keywords: Machine learning and data analytics in process control, Reinforcement learning and deep learning in control, Data-driven control
Abstract: We propose a framework for the design of feedback controllers that combines the optimization-driven and model-free advantages of deep reinforcement learning with the stability guarantees provided by using the Youla-Kucera parameterization to define the search domain. Recent advances in behavioral systems allow us to construct a data-driven internal model; this enables an alternative realization of the Youla-Kucera parameterization based entirely on input-output exploration data. Using a neural network to express a parameterized set of nonlinear stable operators enables seamless integration with standard deep learning libraries. We demonstrate the approach on a realistic simulation of a two-tank system.
|
|
11:00-11:20, Paper ThA15.4 | |
Reinforcement Learning with Partial Parametric Model Knowledge |
|
Wang, Shuyuan | UBC |
Loewen, Philip D. | Univ. of British Columbia |
Lawrence, Nathan P. | University of British Columbia |
Forbes, Michael Gregory | Honeywell |
Gopaluni, Bhushan | University of British Columbia |
Keywords: Machine learning and data analytics in process control, Learning for control, Machine learning in modelling, prediction, control and automation
Abstract: We adapt reinforcement learning methods for continuous control to bridge the gap between complete ignorance and perfect knowledge of the environment. Our method, Partial Knowledge Least Squares Policy Iteration (PLSPI), takes inspiration from both model-free RL and model-based control. It uses incomplete information from a partial model and retains RL’s data-driven adaption towards optimal performance. The linear quadratic regulator provides a case study; numerical experiments demonstrate the effectiveness and resulting benefits of the proposed method.
|
|
11:20-11:40, Paper ThA15.5 | |
A Weekday and Weekend Separation-Based Algorithm for Short-Term Load Forecasting |
|
Shim, Sang Woo | Konkuk University |
Hwang, Sun Young | Konkuk University |
Lee, Da-Han | Konkuk University |
Roh, Jae-Hyung | Konkuk University |
Park, Jong-Bae | Konkuk University |
Keywords: Machine learning methods and applications
Abstract: This paper presents a methodology for forecasting hourly loads over seven days, using a separation of weekday and weekend data. The data used for the forecasting included the date, weather, and load data from January 1, 2021, with the forecast being conducted for four weeks from November 1 to 28, 2021. The methodology involved separating the data into weekdays and weekends, conducting separate forecasts for each, selecting features for use in each process, and optimizing the forecasting model's parameters through hyperparameter tuning. To select features, the Shapley Additional Explanations method was used to calculate feature importance, and Pearson correlation coefficients were used to measure linearity between features. This allowed for the selection of input features with high importance while avoiding those with high linearity with other features. The parameters of the forecasting model were optimized through Grid search, and the optimal combination of the XGBoost forecasting model's Learning Rate, n estimators, and Max depth was assessed. After all processes were completed, forecasting was performed, and the forecasting error was presented through Normalized Mean Absolute Error, Mean Absolute Percentage Error, and Normalized Root Mean Squared Error. The results obtained using the proposed algorithm were compared with those obtained without using it. In future studies, the authors plan to investigate forecasting for special dates, such as public holidays, and explore the use of forecasting algorithms that consider the probability of input data.
|
|
11:40-12:00, Paper ThA15.6 | |
Linear-Quadratic Flotation Level Control through Reinforcement Learning |
|
Norlund, Frida | Lund University |
Tammia, Rasmus | Boliden Mineral AB |
Hagglund, Tore | Lund University |
Soltesz, Kristian | Lund University |
Keywords: Machine learning methods and applications, Advanced process control, Process optimisation
Abstract: In the mining industry, flotation is a commonly used process to separate valuable minerals from waste rock in a concentrator. The rougher flotation is the first stage of the process and in Boliden AB's concentrator at Aitik, it consists of two lines of four flotation cells. In this paper we consider one line of four cells and the buffer tank upstream of them. The operating conditions in the flotation process change as the ore quality varies. This is a challenge when modeling the process. We address this challenge by using a reinforcement learning (RL) algorithm to design a state feedback controller for level control, without the need of an explicit process model. Using simulations, we compare the performance of the resulting controller to that of the cascade coupled PI-control structure that operates the real plant today. The RL-based controller improves the performance and shows good potential. Convergence to an admissible control law requires careful hyper-parameter tuning. Industrial deployment thus requires further work to ensure the required reliability.
|
|
ThA16 |
Room 416 |
Tracking and Navigation |
Regular Session |
Chair: Kobayashi, Koichi | Hokkaido University |
Co-Chair: Sharma, Shambhu N. | National Institute of Technology, Surat, Gujarat |
|
10:00-10:20, Paper ThA16.1 | |
Reciprocal Safety Velocity Cones for Decentralized Collision Avoidance in Multi-Agent Systems |
|
Berkane, Soulaimane | Université Du Québec En Outaouais |
Dimarogonas, Dimos V. | KTH Royal Institute of Technology |
Keywords: Decentralized control, Cooperative navigation, Trajectory and path planning
Abstract: In this paper, we solve the inter-agent collision avoidance problem in an arbitrary n-dimensional Euclidean space using reciprocal safety velocity cones (RSVCs). We propose a decentralized feedback control strategy that guarantees simultaneously asymptotic stabilization to a reference and collision avoidance. Our algorithm is purely decentralized in the sense that each agent uses only local information about its neighbouring agents. Moreover, the proposed solution can be implemented using only inter-agent bearing measurements. Therefore, the algorithm is a sensor-based control strategy which is practically implementable using a wide range of sensors such as vision systems and range scanners. Simulation results in a two dimensional environment cluttered with agents shows that the number of possible deadlocks is marginal and decrease with the decrease in the clutteredness of the workspace.
|
|
10:20-10:40, Paper ThA16.2 | |
Gradient-Based Cooperative Control of Quasi-Linear Parameter Varying Vehicles with Noisy Gradients |
|
Datar, Adwait | Institute of Control Systems, Hamburg University of Technology |
Mendez Gonzalez, Antonio | Hamburg University of Technology |
Werner, Herbert | Hamburg University of Technology |
Keywords: Linear parameter-varying systems, Robust control, Nonlinear cooperative control
Abstract: This paper extends recent results on the exponential performance analysis of gradient based cooperative control dynamics using the framework of exponential integral quadratic constraints. A cooperative source-seeking problem is considered as a specific example where one or more vehicles are embedded in a strongly convex scalar field and are required to converge to a formation located at the minimum of a field. A subset of the agents are assumed to have the knowledge of the gradient of the field evaluated at their respective locations and the interaction graph is assumed to be uncertain. As a first contribution, we extend earlier results on linear systems to non-linear systems by using quasi-linear parameter varying representations. Secondly, we remove the assumption on perfect gradient measurements and consider multiplicative noise in the analysis. Performance-robustness trade off curves are presented to illustrate the use of presented methods for tuning controller gains. The results are demonstrated on a group of non-linear second order vehicles with a velocity-dependent non-linear damping and a local gain-scheduled tracking controller.
|
|
10:40-11:00, Paper ThA16.3 | |
Automatic Generation of Control Lyapunov Functions for Vehicle Guidance on Complex Paths |
|
Yamashita, Yuh | Hokkaido University |
Hashimoto, Wataru | Hokkaido University |
Kobayashi, Koichi | Hokkaido University |
Keywords: Lyapunov methods, Autonomous mobile robots, Constrained control
Abstract: In this paper, we propose a new method to construct systematically a control Lyapunov function (CLF) for vehicle guidance and obstacle avoidance. The obtained CLF is expressed by some parameters, and the exact values of the CLF and its gradient can be computed online. The rough route of the vehicle to the goal point is designed by a directed acyclic graph (DAG). The asymptotic stability of the controller based on the designed CLF is mathematically guaranteed. The method can be applied to cases with obstacles having complex shapes. By modifying the DAG and some values, we can change the rough route of the vehicle as well as the goal point.
|
|
11:00-11:20, Paper ThA16.4 | |
Some Issues about FL and LAB Servo Control |
|
Albertos, Pedro | Univ. Politecnica De Valencia |
Scaglia, Gustavo | Universidad Nacional De San Juan |
Wei, Cui | Northeastern University |
Yuz, Juan I. | Universidad Técnica Federico Santa María |
Keywords: Tracking, Application of nonlinear analysis and design, Stability of nonlinear systems
Abstract: In this paper, the servo control design methodologies based on Feedback Linearization (FL) and Linear Algebra Based (LAB) are applied to nonlinear systems with and without zero dynamics, analysing the case of unstable zero dynamics. Their advantages and drawbacks are discussed. Some examples are developed to illustrate the results.
|
|
11:20-11:40, Paper ThA16.5 | |
6D Object Pose Tracking with Optical Flow Network for Robotic Manipulation |
|
Chen, Tao | University of Essex |
Gu, Dongbing | University of Essex |
Keywords: Tracking, Perception and sensing, Robots manipulators
Abstract: In this paper, we design a novel 6-DOF object pose tracking framework for robotic manipulation tasks. The framework takes a RGB-D video stream as input observations and outputs a 6D pose estimate corresponding to each frame for the interested object to be tracked. The novelty lies in the pose change estimation where we leverage a segmentation network and an optical flow network to estimate the pose change between previous and current frames. The final 6D pose estimate is the multiplication of the 6D pose matrix in previous frame and the pose change. Unlike most tracking networks, our pose tracking model does not require any object 3D model as auxiliary input. We take two consecutive frames as the input and estimate their optical flow map by using a pre-trained optical flow network. Our framework is a keypoint based estimation method. The estimated flow map can extract the temporal motion information that can be used to generate keypoint candidates. Then an iterative keypoint refinement scheme is used to validate the selected keypoints. Our experimental results show that our framework can outperform some existing works or achieve comparable results in three selected datasets.
|
|
11:40-12:00, Paper ThA16.6 | |
Speed and Range Parameterised State Estimators for 3D Underwater Angles-Only Target Tracking Problem |
|
Asfia, Urooj | Sardar Vallabhbhai National Institute of Technology, Surat |
Radhakrishnan, Rahul | Sardar Vallabhbhai National Institute of Technology, Surat |
Sharma, Shambhu N. | National Institute of Technology, Surat, Gujarat |
Keywords: Tracking, Kalman Filtering, Estimation and filtering
Abstract: An angles-only underwater target tracking problem in three-dimensional space is considered in this work. The uncertainty in the initial range and speed parameters of the target can lead to a loss of accuracy. Hence, a parametrised state estimation approach is opted to achieve better estimation performance for the nonlinear filtering algorithms. To achieve this, the unscented Kalman filter (UKF) and new sigma point Kalman filter (NSKF) has been reformulated by incorporating the speed and range parametrisation concept. A comparison analysis considering different sampling intervals is performed based on root mean square error (RMSE) in position, percentage track loss, and bias norm, for a moderately nonlinear tracking scenario.
|
|
ThA17 |
Room 417 |
FDI and FTC I |
Regular Session |
Chair: Kinnaert, Michel | Université Libre De Bruxelles |
Co-Chair: Liu, Qiang | Northeastern University |
|
10:00-10:20, Paper ThA17.1 | |
In-Flight Monitoring of a Primary Flight Control Electromechanical Actuator |
|
Wauthion, Benjamin | Université Libre De Bruxelles |
Telteu-Nedelcu, Dan | Société Anonyme Belge De Constructions Aéronautiques |
Alexandre, Paul | Société Anonyme Belge De Constructions Aéronautiques |
Kinnaert, Michel | Université Libre De Bruxelles |
Keywords: Applications of FDI and FTC, Parameter estimation based methods for FDI, FDI for nonlinear Systems
Abstract: We aim at designing a monitoring algorithm able to perform early detection of degradation that may lead to jamming in the electromechanical actuators (EMAs) used for primary flight control. The challenge is to construct a detection algorithm performing an online monitoring using in-flight data. As the EMAs only move during specific phases of flight, the data subsets containing relevant information for the identification of at least some friction parameters must be determined. This is achieved by using tools from sensitivity analysis. The resulting data analysis is used to govern the parameter estimation part of a Dual Extended Kalman Filter (DEKF) in such a way that all informative data are exploited at best for friction estimation. The method is validated on healthy and faulty synthetic data resulting from a detailed EMA simulator.
|
|
10:20-10:40, Paper ThA17.2 | |
Leakage Diagnosis Framework for Water Distribution Networks Using ABC |
|
Rathore, Saruch Satishkumar | Aalborg University, Denmark |
Kallesøe, Carsten Skovmose | Grundfos |
Wisniewski, Rafal | Aalborg University |
Keywords: Applications of FDI and FTC, Parameter estimation based methods for FDI, FDI for nonlinear Systems
Abstract: In this work, we present a novel approach for leakage localization and identification in water distribution networks using Approximate Bayesian Computation(ABC). A reduced pressure graph theory-based model is derived for the water networks. A leakage is considered an unknown parameter of the model which is to be estimated. Consumer demands are considered stochastic in nature and owing to that the model output, which is pressure, is also stochastic. The first moment of the model and the pressure measurements are compared to estimate probable leakages. Further, the probability distribution for the estimated leakages is computed using ABC. Results from an experimental test on a small-scale water network are also presented to demonstrate the approach.
|
|
10:40-11:00, Paper ThA17.3 | |
A Novel Fault Classification Method for Process Industries Incorporating Multi-Sphere Support Tensor Data Description and Hybrid Synchronization Optimization |
|
Zhang, Chuanfang | University of Science and Technology Beijing |
Peng, Kaixiang | Univ of Science and Technology, Beijing, China |
Dong, Jie | Univ of Science and Technology, Beijing, China |
Ma, Liang | University of Science and Technology Beijing |
Zhang, Xueyi | University of Science and Technology Beijing |
Keywords: AI methods for FDI, FDI based on qualitative models, Applications of FDI and FTC
Abstract: Process monitoring is important for ensuring the safe running of process industries. From the perspective of pattern recognition, fault detection can be regarded as a binary classification problem, while fault classification can be regarded as a multi-class classification issue. As the extension of one-class classifier, multi-sphere support vector data description (MSVDD) are oriented to vector data and cannot deal with tensor data directly. Moreover, MSVDD cannot deal with feature selection and parameter optimization synchronously. In order to deal with above problems, a faut classification method based on multi class support tensor data description (MSTDD) is proposed in this paper. Based on sooty tern optimization algorithm (STOA) and beetle antennae search (BAS), a hybrid synchronization optimization (HSO) strategy is used to select features and optimize parameters at the same time. Application to the Tennessee Eastman process (TEP) verifies the classification performance of HSO-MSTDD comparing to MSTDD.
|
|
11:00-11:20, Paper ThA17.4 | |
Fault Diagnosis of Drilling Process Based on Multi-Scale Decomposition and Decision Fusion |
|
Yang, Aoxue | China University of Geosciences |
Wu, Min | China University of Geosciences |
Yu, Wanke | School of Automation, China University of Geosciences No. 388 , |
Hu, Jie | China University of Geosciences |
Lu, Chengda | China University of Geosciences |
Nakanishi, Yosuke | Waseda University |
Keywords: AI methods for FDI, Applications of FDI and FTC, Methods based on neural networks and/or fuzzy logic for FDI
Abstract: Data-driven fault diagnosis methods have been widely applied at present. In the drilling process, there usually exists multiple failure modes resulting in the multi-scale of drilling fault data, which would bring challenges for the data-driven methods application in drilling. By considering the characteristics of multi-scale and multivariate, an original scheme based on mode decomposition and decision fusion is proposed for fault diagnosis of drilling process. Firstly, the raw data are decomposed and reconstructed into multiple groups of series. Then, for each group, the diagnosis model is established using the convolutional neural network (CNN), and several diagnostic results are obtained. Finally, all diagnostic results are fused by the Dempster-Shafer (D-S) evidence theory, and the fused result is taken as the final diagnostic result. The actual data based experiments illustrate the effectiveness of proposed method for improving the performance of drilling fault diagnosis.
|
|
11:20-11:40, Paper ThA17.5 | |
A Novel Multi-Dimensional Time-Series Data Anomaly Detection Model Based on Generative Adversarial Network Aided Autoencoder |
|
Gong, Zejun | Northeastern University |
Liu, Qiang | Northeastern University |
Ding, Jinliang | Northeastern University |
Wang, Xiaobo | Northeastern University |
Wang, Peng | Fudan University |
Keywords: AI methods for FDI, Condition monitoring, Process performance monitoring/statistical process control
Abstract: With increasing amount and easiness of access the data in industrial processes, data-driven technologies have become more prevalent in process monitoring. Anomaly detection is an indispensable part of process monitoring. However, most industrial data are closely related to time, and classical anomaly detection algorithms mostly focus on learning the features of static data, ignoring the dynamic features of industrial data. This paper proposes a multi-dimensional time-series data anomaly detection model based on generative adversarial network aided autoencoder. By extracting the features of the normal time-series data, feature representation is established in latent space. Meanwhile, we introduce generated adversarial network (GAN) into the autoencoder (AE) training to enhance the feature learning ability of the autoencoder, so that the normal time-series data can be well represented in the latent space. Gated recurrent unit (GRU) is used as the main network of the autoencoder to learn the dynamic features between different time steps in the sequence data and detect fault data through the value of the reconstruction error. We verify the validity of the proposed model in simulation data and apply it to the real anomaly detection of steel plate production. Compared with k-nearest neighbor, linear discriminant analysis, principal component analysis, one-class support vector machine, data-enhanced method and the traditional dynamic autoencoder, the proposed method performs the best.
|
|
ThA18 |
Room 418 |
Adaptive and Learning Control for Robotics and Dynamical Systems |
Open Invited Session |
Chair: Palis, Stefan | University Magdeburg |
Co-Chair: Sato, Takao | University of Hyogo |
Organizer: Azar, Ahmad Taher | College of Computer & Information Sciences, Prince Sultan University |
|
10:00-10:20, Paper ThA18.1 | |
Neural Network Based Adaptive Control of Gantry Cranes (I) |
|
Otto, Eric | Otto Von Guericke University Magdeburg |
Maksakov, Anton | Otto-Von-Guericke University Magdeburg |
Golovin, Ievgen | Otto Von Guericke University Magdeburg |
Palis, Stefan | University Magdeburg |
Keywords: Adaptive control, System identification and adaptive control of distributed parameter systems, Lyapunov methods
Abstract: During the operation of large gantry cranes oscillations of flexible structures causedby the trolley movement lead to undesired wear of the construction and deteriorate the efficiency of the crane operation. Therefore, a neural network based adaptive control system for tracking control of the payload position and damping of oscillations is presented and validated in numerical simulations. By comparison to a previously derived nonlinear controller, it is shown that the proposed control law achieves good tracking and damping results with minimal a priori knowledge of the crane dynamics and without knowledge about specific plant parameters, therefore reducing the required modeling effort significantly.
|
|
10:20-10:40, Paper ThA18.2 | |
ADArduPilot: An ArduPilot Compatible Adaptive Autopilot (I) |
|
Li, Peng | Southeast University |
Liu, Di | Technical University of Munich |
Xia, Xin | Southeast University |
Baldi, Simone | Southeast University |
Keywords: Adaptive control, UAVs, Application of nonlinear analysis and design
Abstract: We release an autopilot that is fully compatible with all the vehicle types the ArduPilot suite was designed for (copters, multi-copters, fixed-wing aircraft, rovers, surface vessels, etc.). The main feature of this autopilot is that adaptation capabilities are embedded without modifying the original ArduPilot architecture, hence the name ADArduPilot. We test the proposed autopilot in several scenarios requiring adaptation (different payloads, different vehicle mass, environmental disturbances), showing that the proposed adaptation mechanism can consistently deliver improved performance in terms of tracking error and control effort.
|
|
10:40-11:00, Paper ThA18.3 | |
Fractional-Order Fixed-Time Non-Singular Sliding Mode Control for Nonlinear Robotic Manipulators (I) |
|
Ahmed, Saim | Automated Systems and Soft Computing Lab (ASSCL), College of Com |
Azar, Ahmad Taher | College of Computer & Information Sciences, Prince Sultan Univer |
A. Hameed, Ibrahim | Norwegian University of Science and Technology (NTNU) |
Keywords: Sliding mode control
Abstract: In this study, fractional-order non-singular fixed-time terminal sliding mode control (FoFxNTSM) for nonlinear robotic manipulators in the existence of uncertainties and external disturbances is examined. To begin, the concept of fractional-order fixed-time non-singular terminal sliding mode control is introduced. This method combines the benefits of NTSM (which provides fast convergence speed, smooth and singularity-free control inputs) with the advantages of a fractional-order constants (which improves position tracking effectiveness). Lyapunov analysis yields the fixed-time stability of the closed-loop system. To evaluate and illustrate the performance of the proposed strategy, the relevant simulation results are presented.
|
|
11:00-11:20, Paper ThA18.4 | |
Deep Learning-Based Output Tracking Via Regulation and Contraction Theory (I) |
|
Zoboli, Samuele | LAGEPP - University Lyon 1 |
Janny, Steeven | LIRIS, INSA Lyon |
Giaccagli, Mattia | Tel Aviv University |
Keywords: Tracking, Data-based control
Abstract: In this paper, we deal with output tracking control problems for input-affine nonlinear systems. We propose a deep learning-based solution whose foundations lay in control theory. We design a two-step state-feedback controller: a contraction-based feedback stabilizer and a feedforward action. To alleviate the need for heavy analytical computations or online optimization, we rely on deep neural networks and link their approximation error to the tracking one. Mimicking the analytical control structure, we split the learning task into two separate modules. We test our solution in a challenging environment to validate the proposed design.
|
|
11:20-11:40, Paper ThA18.5 | |
Adaptive Decentralized Stabilization of Infinite Networks of Interconnected Nonlinear Systems with Uncontrollable Linearization |
|
Pavlichkov, Svyatoslav | Technical University of Kaiserslautern |
Bajcinca, Naim | University of Kaiserslautern |
Keywords: Decentralized control, Networked systems, Adaptive control
Abstract: We solve the problem of decentralized adaptive stabilization for infinite networks of interconnected nonlinear systems in lower-triangular form with power integrators, with uncontrollable linearization and with uncertainties in control directions. The feedback law is adaptive and continuous but not necessarily smooth, and the decentralized adaptive backstepping algorithm is based on small gain stability conditions for infinite networks.
|
|
11:40-12:00, Paper ThA18.6 | |
Design Finite-Time Consensus Protocol for High-Order Linear Multi-Agent Systems: A Gain Scheduled Approach |
|
Zhou, Yuan | Northwestern Polytechnical University |
Liu, Yongfang | Peking University |
Zhao, Yu | Northwestern Polytechnical University |
Keywords: Adaptive control, Linear systems
Abstract: This paper revisits the finite-time consensus problem for high-order linear multi-agent networks by using smooth state-feedback. By following a gain scheduled approach, this paper first presents finite-time consensus protocol with a state-independent parameter, which takes the time-varying solution of parametric Lyapunov equation to design control gain.Note that the state-independent parameter is selected based on the connectivity of topology, which is a piece of global information. To get rid of this dependence, a node-based adaptive parameter is further proposed to achieve fully distributed consensus. Through finite-time stability theory, both the prepared parameters, including state-independent and adaptive parameters, for control protocol make the agents achieve finite-time consensus. Particularly, a specific convergence time is given by following the concept of finite-time escaping function. Finally, we provide a practical simulation on finite-time formation problem of six satellites, demonstrating the validity of theoretical results.
|
|
ThA19 |
Room 419 |
Hybrid and Sliding Mode Control |
Regular Session |
Chair: Gaspar, Peter | SZTAKI, Institute for Computer Science and Control (SZTAKI), Eotvos Lorand Research Network (ELKH) |
Co-Chair: Aguilar, Luis T. | Instituto Politecnico Nacional |
|
10:00-10:20, Paper ThA19.1 | |
Ultra-Local Model-Based Observer Design for Automated Vehicles |
|
Fényes, Dániel | Institute for Computer Science and Control (SZTAKI) |
Hegedűs, Tamás | Budapest University of Technology and Economics |
Nemeth, Balazs | SZTAKI |
Gaspar, Peter | SZTAKI, Institute for Computer Science and Control (SZTAKI), Eot |
Keywords: Observer design, Adaptive and robust control of automotive systems, Parameter and state estimation
Abstract: This paper presents a novel observer design method that combines the Linear Quadratic (LQ) and ultra-local model-based approaches. Firstly, the LQ observer design is performed, which uses the nominal model of the system. Then, the ultra-local model-based solution is introduced. The results of the LQ observer are augmented with the ultra-local model, which aims to increase the accuracy of the estimation process even for systems with high nonlinearities. During the implementation process, in the nominal observer, the parameter uncertainties are not taken into account. These effects are also considered with the application of the ultra-local model. The design process is carried out for an automated vehicle-related observation problem, the lateral velocity estimation. Finally, the whole observer algorithm is implemented in high-fidelity vehicle dynamics simulation software to show its effectiveness.
|
|
10:20-10:40, Paper ThA19.2 | |
Prescribed-Time Output Feedback Performance Assessment: Comparative Study |
|
Verdés Kairuz, Ramón Imad | Instituto Politécnico Nacional |
Orlov, Yury | CICESE |
Aguilar, Luis T. | Instituto Politecnico Nacional |
Keywords: Discontinuous control, Output feedback control, Disturbance rejection
Abstract: Control loop performance assessment is addressed in the context of the output feedback stabilization in fixed-time. Existing fixed- and prescribed-time output feedback control algorithms are reviewed and their pros and cons are discussed for performing the afore-mentioned task. The control performance assessment is based on integral indices. These indices are computed from the available data obtained from numerical simulations with a simple pendulum system affected by matched disturbances and measurement noise. Simulation results corroborates the pros and cons of the fixed-time output feedback algorithms in question.
|
|
10:40-11:00, Paper ThA19.3 | |
An Improved Model-Free Adaptive Integral Sliding Mode Control for a Class of Nonlinear Discrete-Time Systems (I) |
|
Xia, Rui | China University of Petroleum (East China) |
Song, Xiaohang | China University of Petroleum (East China) |
Sun, Jiaxin | Huanghai University |
Zhao, Dongya | China University of Petroleum (East China) |
Spurgeon, Sarah K. | University College London |
Keywords: Sliding mode control, Robust estimation, Data-driven optimal control
Abstract: For a class of uncertain single-input single-output (SISO) nonlinear discrete-time systems, an improved model-free adaptive integral sliding mode control (MFA-ISMC) algorithm is proposed based on a disturbance observer. The pseudo-partial derivative (PPD) estimation algorithm used to describe the system dynamics is modified and the stability of the closedloop system is guaranteed. It is shown that the corresponding closed-loop system performance is improved and the effectiveness of the proposed method is demonstrated by a simulation example.
|
|
11:00-11:20, Paper ThA19.4 | |
Energy-To-Peak Static Output Control for Continuous-Time Hidden Markov Jump Linear Systems |
|
Costa, Oswaldo Luiz do Valle | Univ. of Sao Paulo |
Marcorin de Oliveira, André | UNIFESP |
Gabriel, Gabriela W. | ITA |
Barros dos Santos, Sérgio Ronaldo | Federal University of Sao Paulo |
Keywords: Control of hybrid systems, Switching stability and control, Fault-tolerant
Abstract: We study the L2-L∞ static output feedback control, also known as energy-to-peak control, for continuous-time Markov jump systems in a context of partial observation of the Markov chain. We consider that the controller has only access to an observed process related to the Markov chain of the plant by means of an exponential hidden Markov model. Sufficient conditions for the design of output feedback controllers satisfying an upper bound on the L2-L∞ ratio are given in terms of Linear Matrix Inequalities (LMIs). Based on this result a coordinate descent algorithm is presented to reduce the L2-L∞ upper bound ratio, starting from a feasible solution for the LMIs restrictions. The paper is conclude with a numerical example to illustrate the results.
|
|
11:20-11:40, Paper ThA19.5 | |
Neural Network-Based Adaptive Sliding Mode Control for Uncertain Singular Semi-Markov Jump Systems with Disturbance and Injection Attack (I) |
|
Liu, Qi | Shanghai Jiao Tong University |
Li, Jianxun | Shanghai Jiao Tong University |
Ma, Shuping | Shandong University |
Wang, Jimin | Chinese Academy of Sciences |
Jiang, Baoping | Ocean University of China |
Keywords: Control of hybrid systems, Sliding mode control, Robust linear matrix inequalities
Abstract: This paper investigates the problem of the observer-based sliding mode control (SMC) against actuator attacks for uncertain singular semi-Markov jump systems (S-MJSs) with unmeasured states, time-varying delay, and exogenous disturbance. An observer-based adaptive neural SMC scheme is put forward to solve the problem. First, considering unmeasured states, a distinctive non-fragile observer, which does not contain control input, is established. Then, “only one sliding surface” route is presented, and the derived sliding surface is accessibly designed. Next, a new stochastic admissibility and passivity sufficient condition is proposed in the forms of linear matrix inequalities (LMIs), and a new algorithm is given to solve the controller gain and the observer gain. Further, a novel observer-based adaptive neural sliding mode controller is proposed to guarantee the sliding surface reachability and stabilize the singular S-MJSs against actuator attacks. Finally, DC motor system can be simulated to demonstrate the effectiveness of the proposed theory.
|
|
11:40-12:00, Paper ThA19.6 | |
Zeros and Zero Dynamics of Switching Systems |
|
Conte, Giuseppe | Universita' Politecnica Delle Marche |
Perdon, Anna Maria | Accademia Marchigiana Di Scienze, Lettere Ed Arti |
Zattoni, Elena | Alma Mater Studiorum Universita' Di Bologna |
Wyman, Bostwick | Ohio State University |
Keywords: Linear systems, Structural properties, Switching stability and control
Abstract: A notion of zero dynamics for switching linear systems is introduced by using a structural geometric approach. The zero dynamics for a switching system is shown to be represented by a family of dynamics that characterize the way in which the stability of each mode is affected when the overall system is made maximally unobservable by means of a state feedback. The comparison between the elements of the zero dynamics of a switching system and the classical zero dynamics of each mode shows differences that are due to the dynamics generated by the switching and by the interaction between the modes. The role of the zero dynamics in characterizing the stability of the compensated system is similar to that found in the classical linear case, although the results in the switching framework are weaker.
|
|
ThA20 |
Room 421 |
Recent Trends in Modeling, Simulation and Control of Distributed Parameter
Systems I |
Open Invited Session |
Chair: Le Gorrec, Yann | FEMTO-ST, ENSMM |
Co-Chair: Ramirez, Hector | Universidad Federico Santa Maria |
Organizer: Le Gorrec, Yann | FEMTO-ST, ENSMM |
Organizer: Ramirez, Hector | Universidad Tecnica Federico Santa Maria - AC3E FB0008 |
|
10:00-10:20, Paper ThA20.1 | |
Mean-Square Exponential Stabilization of Coupled Hyperbolic Systems with Random Parameters (I) |
|
Auriol, Jean | CNRS, Centrale Supelec |
Pereira, Mike | Chalmers University of Technology |
Kulcsar, Balazs | Chalmers University of Technology |
Keywords: Backstepping control of distributed parameter systems, Control of hyperbolic systems and conservation laws, Probabilistic robustness
Abstract: In this paper, we consider a system of two coupled scalar-valued hyperbolic partial differential equations (PDEs) with random parameters. We formulate a stability condition under which the classical backstepping controller (designed for a nominal system whose parameters are constant) stabilizes the system. More precisely, we guarantee closed-loop mean-square exponential stability under random system parameter perturbations, provided the nominal parameters are sufficiently close to the stochastic ones on average. The proof is based on a Lyapunov analysis, the Lyapunov functional candidate describing the contraction of L^2-norm of the system states. An illustrative traffic flow regulation example shows the viability and importance of the proposed result.
|
|
10:20-10:40, Paper ThA20.2 | |
Backstepping-Based Rapid Stabilization of Two-Layer Timoshenko Composite Beams (I) |
|
Chen, Guangwei | Zhejiang University |
Vazquez, Rafael | Universidad De Sevilla |
Krstic, Miroslav | Univ. of California at San Diego |
Keywords: Backstepping control of distributed parameter systems, Control and estimation of wave equations and systems of elasticity
Abstract: n this paper, we investigate the rapid stabilization of two-layer Timoshenko composite beams with anti-damping and anti-stiffness at the uncontrolled boundaries. This work extends our previous result on single-layer Timoshenko beams. While the problem of stabilization for two-layer composite beams has been previously studied, the obtention of an arbitrarily fast decay rate is a novel result, as well as considering anti-damping and anti-stiffness in the boundaries (which can possibly lead to rapid divergence). Our approach is based on the introduction of a Riemann transformation of the states of two-layer Timoshenko beams into a 1-D hyperbolic PIDE-ODE system. Then, PDE backstepping is used to design a control law resulting in closed-loop stability of the origin in the L2 sense. An arbitrarily rapid convergence rate can be obtained by adjusting control parameters. The control law is also extended to the case of having longitudinal dynamics, obtaining a similar result.
|
|
10:40-11:00, Paper ThA20.3 | |
Optimal Actuator Location for Diffusion Equation with Neumann Boundary Control (I) |
|
Yang, Kaijun | University of Waterloo |
Morris, Kirsten A. | Univ. of Waterloo |
Keywords: Optimal control of partial differential equations, Optimal control theory
Abstract: This paper is concerned with optimal actuator location for a class of diffusion equations with boundary control. The problem of optimal actuator location based on a linear quadratic cost in case of the worst initial condition is formulated. This leads to a cost involving the operator norm of the Riccati operator. The existence of optimal locations within the uniform operator norm is guaranteed. A Galerkin-based algorithm for approximating the optimal locations and the convergence of the approximation of the optimal locations is also presented.
|
|
11:00-11:20, Paper ThA20.4 | |
Backstepping-Based Tracking Control of the Vertical Gradient Freeze Crystal Growth Process (I) |
|
Ecklebe, Stefan | TU Dresden |
Gehring, Nicole | Johannes Kepler University Linz |
Keywords: Backstepping control of distributed parameter systems, Control of heat and mass transfer systems, Thermal and process control applications of distributed parameter systems
Abstract: The vertical gradient freeze crystal growth process is the main technique for the production of high quality compound semiconductors that are vital for today’s electronic applications. A simplified model of this process consists of two 1D diffusion equations with free boundaries for the temperatures in crystal and melt. Both phases are coupled via an ordinary differential equation that describes the evolution of the moving solid/liquid interface. The control of the resulting two-phase Stefan problem is the focus of this contribution. A flatness-based feedforward design is combined with a multi-step backstepping approach to obtain a controller that tracks a reference trajectory for the position of the phase boundary. Specifically, based on some preliminary transformations to map the model into a time-variant PDE-ODE system, consecutive decoupling and backstepping transformations are shown to yield a stable closed loop. The tracking controller is validated in a simulation that considers the actual growth of a Gallium arsenide single crystal.
|
|
11:20-11:40, Paper ThA20.5 | |
Prediction-Based Stabilization of Multi-Input Nonlinear Systems with Distinct Delays |
|
Fang, Qin | Qufu Normal University |
Zhang, Zhengqiang | Qufu Normal University |
Keywords: Delay compensation for linear and nonlinear systems, Lyapunov methods, Backstepping control of distributed parameter systems
Abstract: We introduce an inexact prediction-based controller for nonlinear systems with single-input unknown delay. The controller is established by an inexact predictor that compensates for the delay robustly, guaranteeing exponential stability for the closed-loop system. As a precondition, we are requested to select a suitable constant in a narrow enough range as the prediction horizon, which can offset the partial effect of the delay. In the end, a simulation example is presented to illustrate the validity of the theoretical results.
|
|
11:40-12:00, Paper ThA20.6 | |
Moving Boundary Observer for Traffic State Estimation with Shock Waves (I) |
|
Luan, Haoran | Beijing University of Technology |
Zhan, Jingyuan | Beijing University of Technology |
Li, Xiaoli | Beijing University of Technology |
Zhang, Liguo | Beijing University of Technology |
Keywords: Observer design, Control of hyperbolic systems and conservation laws, Backstepping control of distributed parameter systems
Abstract: Traffic state estimation is the acquisition of traffic state information from partially observed traffic data, which is crucial to the effectiveness of traffic management and control. This paper investigates the estimation problem of traffic flow state with shock waves in the congestion regime by proposing a moving boundary observer. The macroscopic traffic flow dynamics in the congestion regime is described by the linearized Aw-Rascle-Zhang (ARZ) traffic flow model over a time-varying moving spatial domain, and according to the Rankine-Hugoniot condition and the characteristic velocities of the ARZ model, a novel propagation model of the shock waves is proposed. We propose a moving boundary observer that can estimate the aggregated traffic state by simply measuring the average vehicle velocity at the moving interface of the shock wave. The observer system is constructed from a copy of the plant and by incorporating injections from moving boundary output measurement errors, in which the observer gains are obtained based on the PDE backstepping method. The exponential stability of the observer error system in the L2 norm is proved via Lyapunov analysis. Finally, the validity of the moving boundary observer for traffic state estimation with shock waves is verified by numerical simulations.
|
|
ThA21 |
Room 422 |
Information and Control Systems in the Cyber-Physical Enterprise II |
Open Invited Session |
Chair: Li, Qing | Tsinghua University |
Co-Chair: Panetto, Hervé | CRAN, University of Lorraine, CNRS |
Organizer: Panetto, Hervé | CRAN, University of Lorraine, CNRS |
Organizer: Weichhart, Georg | Primetals |
Organizer: Molina, Arturo | Tecnologico De Monterrey |
|
10:00-10:40, Paper ThA21.1 | |
Review of Smart Cyber City: Keys Requirements, Tools and Issues (I) |
|
Nouiri, Maroua | LS2N - Nantes Université, France |
Bouazza, Wassim | Nantes Université, École Centrale Nantes, CNRS, LS2N, UMR 6004, |
Cardin, Olivier | LS2N UMR CNRS 6004 - Nantes University - IUT De Nantes |
Trentesaux, Damien | LAMIH UMR CNRS 8201, SurferLab, University of Valenciennes and H |
Keywords: Cyber physical system, Internet-of-Things and sensing enterprise, Cyber-physical-social systems
Abstract: With the continuous growth of the urban population, the world is confronting numerous challenges in the near future of cities, related to environmental, economic and social aspects (e.g., traffic congestion, air pollution, waste management, etc.). The smart cyber city concept is introduced as a solution to achieve sustainability, effective management of energy, and smart living. Designing such complex systems with such features is an equally complex challenge. The cyber physical system (CPS) and the Internet of thing (IoT) are keys to achieve the realization of current smart city. In this paper, a survey of smart city vision is given while highlighting the potential benefits of a smart cyber city. A bibliometric network with Vosviewer software was created in order to select the most significant papers. It reviews smart city's key requirements and smart city enabling technologies. It then highlights the potential role of CPS and IoT. Finally, an outline of future research areas is given.
|
|
10:40-11:00, Paper ThA21.2 | |
Electricity System Built on Cyber-Physical Enterprises: Architecture Analysis (I) |
|
Kannisto, Petri | Tampere University |
Supponen, Antti | Tampere University |
Repo, Sami | Tampere University of Technology |
Hästbacka, David | Tampere University |
Keywords: Enterprise interoperability, Internet of services and service science, Cyber physical system
Abstract: Energy distribution systems can improve in adaptiveness by applying the concepts of cyber-physical systems (CPS), cyber-physical enterprise, and service-oriented architecture. With these paradigms, the information and communications technology (ICT) systems can respond to changes in the requirements and conditions of the environment, improving responsiveness to the fluctuation of electricity production from renewable energy sources (RES). This paper analyzes the suitability of a CPS architecture for the electricity distribution system. The novelty comes from a service-oriented model where customers and microgrids can sell services to one another and operators, building added value on existing energy resources. The architecture is analyzed with a coordinated voltage control (CVC) use case. The results suggest that the architecture can open new possibilities in utilizing energy resources and enables a customer-driven, distributed scheme instead of the strict operator-centric hierarchy of the contemporary systems.
|
|
11:00-11:20, Paper ThA21.3 | |
Digital Technologies to Empower Human Activities in Cyber-Physical Systems (I) |
|
Piardi, Luis | Research Centre in Digitalization and Intelligent Robotics (CeDR |
Queiroz, Jonas | Instituto Politécnico De Bragança |
Pontes, Joseane | UTFPR |
Leitão, Paulo | Polytechnic Institute of Bragança |
Keywords: Human-automation integration, Human-centric manufacturing, Cyber physical system
Abstract: Humans play a critical role in cyber-physical systems (CPS) since they are the most flexible piece in this systems. However, their integration is not an easy task and constitutes a significant challenge, presenting different requirements according to the activities they execute and the related integration levels, i.e., Human-in-the-Loop (HitL) and Human-in-the-Mesh (HitM). This paper aims to discuss how emergent digital technologies can empower a smoother and more symbiotic integration of humans in industrial CPS. Particularly, it contributes with an analysis of different aspects and concerns that must be considered to properly enable the HitL and HitM in CPS. Three experimental case studies are presented to demonstrate the feasibility and contribution of using disruptive digital technologies to enhance the human-CPS integration, by assisting them to perform their operations in a faster and more efficient manner.
|
|
11:20-11:40, Paper ThA21.4 | |
A Real-Time Human-In-The-Loop Control Method for Complex Systems (I) |
|
Hu, Chenlian | Alibaba Group |
Wang, Lei | Alibaba Group |
Pei, Cheng | Alibaba Group |
Chen, Meiling | Alibaba Group |
Keywords: Human-automation integration, Production activity control, Modelling and decision making in complex systems
Abstract: Real-time control tasks are of great importance in complex production and manufacturing systems since real-time operation may not proceed as pre-planned mostly. In this paper, we focus on a real-time control problem in a complex system which mainly consists of decision-makers, operators, and mobile machines. Each decision-maker takes charge part of the machines and controls their visiting sequences towards an operator in real time with respect to a variety of practical constraints. Although massive sensing data is available, decision-makers may not be able to process all the data and control too many machines simultaneously in real time owing to their limited computing ability and working memory. To address the problem, we design a human-in-the-loop control method in which decision-makers only need to supervise the control actions generated by a controller and can change these actions based on their real-time observations and judgements. The designed method contains four major parts which are the data processing and checking component, the controller, the exception warning component, and the controller and decision-maker interaction component. We develop a decision support tool based on the proposed method and apply it in a real-life application of controlling the truck arriving sequences at the quay cranes of a container terminal during the loading operation.
|
|
ThA22 |
Room 423 |
Control, Mechatronics, and Imaging for Medical Devices and Systems in
Medicine III |
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 |
|
10:00-10:20, Paper ThA22.1 | |
An Estimation Perspective on Breathing Effort Disturbances in Mechanical Ventilation (I) |
|
van de Kamp, Lars | Eindhoven University of Technology |
Hunnekens, Bram | Eindhoven University of Technology |
van de Wouw, Nathan | Eindhoven Univ of Technology |
Oomen, Tom | Eindhoven University of Technology |
Keywords: Identification and validation, Biomedical system modeling, simulation and visualization, Parameter and state estimation
Abstract: Estimation of relevant lung parameters and the breathing effort of a ventilated patient is essential to keep track of the patient’s clinical condition. The aim of this paper is to investigate the major challenges of estimating the patient’s condition with parametric models. The main method is a linear regression framework, where identifiability and persistence of excitation aspects are clearly unraveled. Different approaches for improving estimation accuracy are outlined. As an illustration, one of the solution strategies is implemented, which leads to accurate estimates of the breathing effort and relevant lung parameters.
|
|
10:20-10:40, Paper ThA22.2 | |
Consideration of Tissue Deformation through an Electrode Displacement in a Monopolar Coagulation Model (I) |
|
Busch, Christoph | Furtwangen University |
Rupitsch, Stefan | University of Freiburg |
Moeller, Knut | Furtwangen University |
Keywords: Biomedical system modeling, simulation and visualization, Physiological Model, Modeling and identification
Abstract: In today's surgery, high-frequency electrical currents are often used to achieve various effects, one important being the heating of tissue to stop bleeding. However, the physical processes of tissue heating are complex and not fully understood. This complicates medical device approval with the settings used for such applications. Therefore, a simulation approach can help provide evidence. In this contribution, we present a modification of a model already presented and described in a previous investigation. By incorporating continuum mechanics into our model, we were able to simulate the deformation of the tissue due to electrode displacement. The resulting deformed configuration was then used to simulate Joule heating by applying a constant direct current voltage and to analyze the effect of varying the electrode displacement depth on the heat distribution result. Our results show that the contact area of the electrode to the tissue plays a crucial role in heating the tissue. This is because the tissue heats up more slowly with a large contact area than with a small one, resulting in significantly greater heat propagation to deeper tissue regions.
|
|
10:40-11:00, Paper ThA22.3 | |
The Effect of Feature Space Separation at Different Training States of CNN (I) |
|
Ding, Ning | Furtwangen University |
Arabian, Herag | Hochschule Furtwangen University, Institute of Technical Medicin |
Moeller, Knut | Furtwangen University |
Keywords: Biomedical system modeling, simulation and visualization
Abstract: Convolutional neural networks (CNNs) are successful in many different applications, however, such model decisions can be easily changed by slight modification on the inputs. The robustness needs to be guaranteed for the safety critical fields like medicine, therefore, it is necessary to understand the decision making procedure of CNN models. As the CNN model automatically extracts the image features and makes the corresponding predictions, observing the learned features space can approximately represent the decision boundary. In this paper, the use of linear interpolation to monitor the learned feature space is applied to analyze the separability property of a CNN model at different classes. By forcing the CNN to learn to separate the extracted features at different layer depths by adding the conformity loss, the classification distribution was more separable and stable to enhance the robustness of the model. The performance of linear interpolation showed the model had better classification abilities, where there are fewer perturbed classes appearing.
|
|
11:00-11:20, Paper ThA22.4 | |
Endotracheal Tube Cuffs for Neonates: Novel Cuff Design to Minimise Tracheal Damage (I) |
|
Edmonds, Alexandra | University of Canterbury |
Clifton, Jaimey A. | University of Canterbury |
Wilkins, Elliott L. | University of Canterbury |
Smith, Chris | University of Canterbury |
Caljé-van der Klei, Trudy | Mechanical Engineering, University of Canterbury |
Guy, Ella F. S. | University of Canterbury |
Lerios, Theodore | University of Canterbury, Christchurch |
Chase, J. Geoffrey | University of Canterbury |
Keywords: Biomedical system modeling, simulation and visualization, Healthcare management, disease control, critical care
Abstract: Neonatal mechanical ventilation (MV) is complex and its efficiency is limited due to leakage of air around the endotracheal tube (ETT). Adult ETT cuffs cannot be used in neonatal patients to block reverse flow as they cause damage to delicate throat tissues. A novel design and testing method for a non-contact neonatal ETT cuff was developed and validated. The goal was to minimise cuff surface area and contact, while creating resistance to airflow using turbulence to reduce ventilator leakage and increase efficacy of treatment for neonatal patients. Several cuff designs were generated based on testing results. Cuffs were tested using flow visualisation methods to assess leak performance in a fluid dynamically scaled experimental test setup. Final cuff designs utilised successful elements from several cuff design iterations. Overall, leakage was reduced by an average of 77.8% from an uncuffed baseline. By increasing the efficacy of healthcare solutions for neonatal patients it is hoped the burden on New Zealand’s NICUs will be reduced, and quality of care increased to improve overall patient outcomes.
|
|
11:20-11:40, Paper ThA22.5 | |
Effects of Velocity Profile and Plate Usage on Identified Bone Strength During Instrumented Screw Insertion (I) |
|
Wilkie, Jack Abraham | Hochschule Furtwangen University |
Bhave, Ashish | Institute of Technical Medicine, Hochschule Furtwangen Universit |
Rauter, Georg | University of Basel |
Moeller, Knut | Furtwangen University |
Keywords: Biomedical system modeling, simulation and visualization, Parameter and state estimation, Modeling and identification
Abstract: Bone screws are important in orthopaedic surgery to treat fractures and secure implants. Over- or under-tightening these screws may lead to premature failure of the screw fixation, necessitating risky and costly revision surgery. Previously, a model-based method for automatically optimising bone screw insertion torque was developed. This paper expands on the prior testing of this method, to investigate how non-ideal conditions may affect the model accuracy/precision. A bone screw was inserted into pre-drilled holes in artificial bone made from PU foam. Three cases were tested: first the screw was inserted directly with a constant velocity, then it was inserted with a trapezoidal velocity profile, and lastly it was inserted with a constant velocity profile, but through a hole in a metal plate. Each case was repeated 20 times for 60 total insertions. Torque and angular displacement measurements were used with a previously-developed model to identify the foam material strength for each insertion. Summary statistics were calculated for each case and statistical tests were used to compare the means and variances for the identified values between each case. Comparing to base base case with constant velocity and no plate: we found a statistically significant (p < 0.05) difference in the mean identified strength for the trapezoidal velocity and the case with the plate. We found a statistically significant difference in the variance for the trapezoidal velocity profile (p < 0.05), but not for case with the plate present (p = 0.16). Future work should investigate these effects over a wider range of materials and screws.
|
|
11:40-12:00, Paper ThA22.6 | |
Finite Element Analysis of a High Compliant Balloon with Strain Sensing Segments for the Identification of Biomechanical Properties within Tubular Vessels (I) |
|
Bhave, Ashish | Institute of Technical Medicine, Hochschule Furtwangen Universit |
Sittkus, Benjamin | Furtwangen University |
Rupitsch, Stefan | University of Freiburg |
Mescheder, Ulrich | Furtwangen University |
Moeller, Knut | Furtwangen University |
Keywords: Biomedical system modeling, simulation and visualization, Bio-signals analysis and interpretation, Identification and validation
Abstract: Conventional methods like Optical Coherence Tomography, Angiography, Fractional Flow Reduction, and Intravascular Ultrasound are used to identify stenosis within arterial vessel segments. These modalities are in fact not ideal to identify the diverse mechanical characteristics of the local tissue. To address the shortcomings, a strain sensing high compliant balloon system for tactile assessment of the vessel lumen is currently investigated in our groups. In this study, four exemplary balloon tissue interactions based on its corresponding 2D traverse cross section are simulated within a Finite Element Analysis (FEA). The simulations were analyzed in respect to the evolving strain states in 5 neighboring sensor elements along the balloon surface. The conducted discussion evaluates the relevance of the obtained interdependencies in respect to an interpretation of the sensor segments, aiming at determining biomechanical properties of the surrounding vessel segment. Thereby, comparisons among the sensor segments and with respect to inflation sequences in the other vessel segments are discussed. Finally, relevant dependencies and design guidelines for strain sensing high compliant balloons are presented, paving the way for future refined FEA studies which ultimately aims for an intraoperative parameter identification with such high compliant sensor balloons. Keywords: FEA, reverse identification, high compliant balloon, strain sensor, biomechanics, artery.
|
|
ThA23 |
Room 501+502 |
Machine Learning in Automotive Powertrains |
Open Invited Session |
Chair: Willems, Frank | Eindhoven University of Technology |
Co-Chair: Shahbakhti, Mahdi | University of Alberta |
Organizer: Willems, Frank | Eindhoven University of Technology |
Organizer: Shahbakhti, Mahdi | University of Alberta |
|
10:00-10:20, Paper ThA23.1 | |
Deep Learning-Based Modeling of Gasoline Controlled Auto-Ignition (I) |
|
Chen, Xu | RWTH Aachen University |
Basler, Maximilian | RWTH Aachen University |
Ketelhut, Maike | Institute of Automatic Control, RWTH Aachen University |
Winkler, Alexander | RWTH Aachen University |
Andert, Jakob | RWTH Aachen University |
Abel, Dirk | RWTH-Aachen University |
Keywords: Engine modelling and control
Abstract: Internal combustion engines face increasingly stringent pollution and greenhouse gas emission restrictions. In this regard, the technology of low-temperature combustion is the scope of research, as it can reduce pollutant emissions while increasing engine efficiency. However, the system dynamics are very complicated and have a high sensitivity concerning the thermodynamics in the combustion chamber. Modeling with first principle models would be time-consuming and requires accurate parameter estimations. Therefore, this work presents deep learning-based models to capture the dynamics of the cylinder pressure trace for gasoline controlled auto-ignition. These models trained with experimental data can learn the internal pattern of the combustion cycle dynamics. Based on information from the current cycle, they enable the prediction of the combustion pressure trace for the following. The results show that the models precisely predict the pressure traces and ensure high prediction accuracy of engine performance parameters derived from the predicted traces. R2 values of 0.95 or more are obtained for global parameters, whereas values of 0.8 or more are obtained for local parameters.
|
|
10:20-10:40, Paper ThA23.2 | |
Integrating Recurrent Neural Networks into Model Predictive Control for Thermal Torque Derating of Electric Machines (I) |
|
Winkler, Alexander | RWTH Aachen University |
Wang, Weizhou | RWTH Aachen University |
Norouzi, Armin | University of Alberta |
Gordon, David | Univ. of Alberta |
Koch, Charles Robert | University of Alberta |
Andert, Jakob | RWTH Aachen University |
Keywords: Nonlinear and optimal automotive control, Control architectures in automotive control, Artificial intelligence in transportation
Abstract: For cost and space reasons, the electric machine (EM) and its cooling system in electrified powertrains for road vehicles are usually designed in such a way that the maximum power cannot be called up continuously. For this purpose, control systems are used that derate the power of the EM depending on its temperature. In this context, this paper presents the integration of a Recurrent Neural Network (RNN) model into a nonlinear model predictive control (MPC) to efficiently control the driving performance of an electric vehicle (EV) on a race track and reduce thermal derating effects. The discrete black-box RNN model incorporating a Long Short-Term Memory (LSTM) layer describing the thermal dynamics of the electric machine is combined with the continuous-time one-dimensional vehicle dynamics to form the hybrid MPC. For the selected example, the RNN-MPC outperforms a standard linear derating strategy by 6.23% in terms of energy consumption while achieving equal lap speed and maximum machine temperatures. Compared to an existing grey-box thermal network model, the RNN model significantly reduces the temperature prediction error by 28%. The trajectory tracking problem is formulated using acados and deployed on a dSPACE SCALEXIO embedded system to meet real-time requirements.
|
|
10:40-11:00, Paper ThA23.3 | |
Cylinder Pressure Feedback Control for Ideal Thermodynamic Cycle Tracking: Towards Self-Learning Engines (I) |
|
Vlaswinkel, Maarten | Eindhoven University of Technology |
Willems, Frank | Eindhoven University of Technology |
Keywords: Engine modelling and control, Control architectures in automotive control, Nonlinear and optimal automotive control
Abstract: To meet increasingly strict future greenhouse gas and pollutant emission targets, development time and costs of heavy-duty internal combustion engines will reach unacceptable levels. This is mainly due to increased system complexity and need to guarantee robust performance under a wide range of real-world conditions. Cylinder Pressure Based Control is a major contributor in achieving these goals. Current Cylinder Pressure Based Control approaces use combustion and air-path parameters as feedback signals. These signals are not directly linked to combustion efficiency; therefore, compensation for changing ambient conditions, engine ageing or differences in fuel qualities is a non-trivial problem. Contrary to other methods, the method presented in this paper aims to realise an idealised thermodynamic cycle by directly control of the entire cylinder pressure curve. From measured in-cylinder pressure, a new set of feedback signals is derived using principle component decomposition. With these signals, optimal fuel path settings are determined. The potential of this method is demonstrated for a dual fuel Reactivity Controlled Compression Ignition engine, which combines very high efficiency and ultra low nitrogen oxides and particle matter emission. For the studied Reactivity Controlled Compression Ignition engine, it is shown that the newly proposed optimisation method gave the same optimal fuel path settings as existing methods. This is an important step towards self-learning engines.
|
|
11:00-11:20, Paper ThA23.4 | |
Turbocharger Control for Emission Reduction Based on Deep Reinforcement Learning (I) |
|
Picerno, Mario | RWTH Aachen University |
Koch, Lucas | RWTH Aachen University |
Badalian, Kevin | RWTH Aachen University |
Lee, Sung-Yong | VKA RWTH Aachen |
Andert, Jakob | RWTH Aachen University |
Keywords: Engine modelling and control, Nonlinear and optimal automotive control, Adaptive and robust control of automotive systems
Abstract: The development of embedded systems is a time-consuming process that relies on the calibration of the control systems by experienced engineers and the availability of prototype vehicles. Modern embedded systems must operate with non-linear functions in a wide range of applications. As a result, even experts are unable to fully comprehend all system interconnections, and optimal performance is rarely achieved. Machine Learning (ML)-based techniques can redefine the conventional approach to decision-making problems in this field. Because Reinforcement Learning (RL) algorithms are self-adaptive, near-optimal solutions can be developed with minimal human intervention, providing significant potential for cost and time savings. In this paper, it is demonstrated how RL can be used to design a control function that competes with and outperforms a state-of-the-art controller, while ensuring the stability of the system. In the Model-in-the-Loop (MiL) framework, a method of accelerated training for the control of the turbocharger is presented that considers both performance and emissions criteria. Data efficiency and training robustness were tested for the Proximal Policy Optimization (PPO) algorithm. Selected policies have been evaluated under transient conditions and are shown to enhance the overall boost pressure accuracy by up to 23%, while reducing cumulative NOx and soot emissions by 4% and 10%, respectively, compared to the reference controller. This work demonstrates another step towards the application of the PPO algorithm in the development of embedded systems for complex control problems. Due to its proven robustness and stability, the method is suitable for transfer to real hardware applications.
|
|
11:20-11:40, Paper ThA23.5 | |
CFD-Based Data-Driven Modeling of Reactivity and Stratification Dynamics for RCCI Engine Control (I) |
|
Khoshbakht Irdmousa, Behrouz | Michigan Technological University |
Naber, Jeffrey | Michigan Technological University |
Shahbakhti, Mahdi | University of Alberta |
Keywords: Automotive system identification and modelling, Engine modelling and control
Abstract: Reactivity Controlled Compression Ignition (RCCI) is a Low-Temperature Combustion (LTC) regime that provides thermal efficiency and emissions benefits compared to traditional Spark Ignition (SI) and Compression Ignition (CI) regimes. However, it is difficult to control combustion at these engines and run them at optimal conditions due to dependency of the their combustion on air-fuel mixture chemical reactivity and fuel stratification inside the combustion chamber. Modeling of reactivity and stratification can provide new pathways to control combustion in RCCI engines. In this study, a data-driven approach based on Computational Fluid Dynamics (CFD) results and a Linear Parameter Varying (LPV) method is proposed to model reactivity and stratification at RCCI engines. This work is illustrated for a real 2-liter 4-cylinder RCCI engine. The results show that the developed data-driven model (DDM) has acceptable prediction accuracy to estimate reactivity and stratification for RCCI engine control. The proposed method can be also implemented in other combustion modes in internal combustion engines.
|
|
11:40-12:00, Paper ThA23.6 | |
Output Feedback Speed Control for a Wankel Rotary Engine Via Q-Learning (I) |
|
Chen, Anthony Siming | University of Manchester |
Herrmann, Guido | University of Manchester |
Burgess, Stuart | University of Bristol |
Brace, Chris | University of Bath |
Keywords: Adaptive and robust control of automotive systems, Nonlinear and optimal automotive control, Engine modelling and control
Abstract: This paper develops a dynamic output feedback controller based on continuous-time Q-learning for the engine speed regulation problem. The proposed controller is able to learn the optimal control solution online in a finite time using only the measurable outputs. We first present the mean value engine model (MVEM) for a Wankel rotary engine. The regulation of engine speed can be formulated as an optimal control problem that minimises a pre-defined value function by actuating the electronic throttle. By parameterising an action-dependent Q-function, we derive a full-state adaptive optimal feedback controller using the idea of continuous-time Q-learning. The adaptive critic approximates the Q-function as a neural network and directly updates the actor, where the convergence is guaranteed by employing novel finite-time adaptation techniques. Then, we incorporate the extended Kalman filter (EKF) as an optimal reduced-order state observer, which enables the online estimation of the unknown fuel puddle dynamics, to achieve a dynamic output feedback engine speed controller. The simulation results of a benchmark 225CS engine demonstrate that the proposed controller can effectively regulate the engine speed to a set point under certain load disturbances.
|
|
ThA24 |
Room 503 |
Modelling, Optimization and Control for Sustainability |
Open Invited Session |
Chair: Robba, Michela | University of Genova |
Co-Chair: Kocijan, Jus | Jozef Stefan Institute |
Organizer: Robba, Michela | University of Genova |
Organizer: Volta, Marialuisa | University of Brescia |
Organizer: Minciardi, Riccardo | Univ of Genova |
Organizer: Sacile, Roberto | Dibris - Unige - Italy |
Organizer: Delfino, Federico | Università Degli Studi Di Genova |
Organizer: Pérès, Francois | ENIT-Toulouse Univ. IFAC TC5.1 & 8.3 Vice Chair |
Organizer: Guariso, Giorgio | Politecnico Di Milano |
Organizer: Ferraris, Luca | CIMA Foundation |
|
10:00-10:20, Paper ThA24.1 | |
A Bi-Level Optimization-Based Architecture for the Scheduling and Real-Time Control of Microgrids with Hydrogen Production System (I) |
|
Bellotti, Daria | University of Genoa |
Ennassiri, Yassine | University of Genoa |
Ferro, Giulio | Università Degli Studi Di Genova |
Magistri, Loredana | University of Genoa |
Robba, Michela | University of Genova |
Keywords: Dynamics and control, Scheduling, coordination, optimization, Decision support and control
Abstract: This paper proposes a novel bi-level architecture for the scheduling and real-time control of a microgrid with a hydrogen production system. It consists of an economic optimization that performs the operational management of the microgrid at the higher level. At the lower level, a real-time controller, based on a Reference Governor (RG), is designed to control the stack’s temperature of a proton exchange membrane (PEM) electrolyzer under the flexible operation imposed by the economic optimization. When switching from one power level to another, the stack’s temperature is having a sudden change that might lead to a violation of the operating limits set by the manufacturer. With the RG-based controller added at the lower level, the operating limits of the temperature are respected, and better performances of the system are guaranteed. The effectiveness of the proposed bi-level architecture has been proved through a real case study, in which the sudden changes in the temperatures have significantly been reduced by up to 91% with respect to the optimal operational management of the overall microgrid.
|
|
10:20-10:40, Paper ThA24.2 | |
Deep Neural Network Adaptation to Different Environmental Contexts: A Case Study of Ozone Forecast (I) |
|
Sangiorgio, Matteo | Politecnico Di Milano |
Guariso, Giorgio | DEIB - Politecnico Di Milano |
Keywords: Machine learning for environmental applications, Modeling and identification of environmental systems, Natural and environmental systems
Abstract: Many environmental variables, in particular, related to air or water quality, are measured in a limited number of points and often for a limited time span. This forbids the development of accurate models for those locations due to an insufficient number of data and poses the question of whether a model developed for another measurement station can be reliably applied. Such a question is particularly critical when the model is constituted by a neural network, i.e., by an approach fully based on local data. In this context, the paper discusses the results of the application of a model to forecast ozone concentrations trained on stations with various characteristics in different environmental settings.
|
|
10:40-11:00, Paper ThA24.3 | |
Geography-Based Neural Networks for the Simulation of Air Pollution (I) |
|
Ferrari, Luca | Politecnico Di Milano |
Guariso, Giorgio | DEIB |
Keywords: Machine learning for environmental applications, Air quality planning and control, Environmental decision support systems
Abstract: Most environmental variables, including air pollution, are characterized by high variability in time and space. The classical approach to modelling these variables is developing physically based models with high data and computational requirements and/or their surrogate version, often implemented through a neural structure. We suggest that adding the geographical coordinates to the other standard inputs of the neural network architectures provides more accurate results without additional measurement costs and with negligible increments of computer time. We demonstrate the advantages of the proposed approach in an application to Northern Italy.
|
|
11:00-11:20, Paper ThA24.4 | |
Land/ocean Absorption Dynamics and Airborne Projection of Carbon Dioxide under Finite Fossil-Fuel Reserves (I) |
|
Novara, Carlo | Politecnico Di Torino |
Mazza, Daniele | Politecnico Di Torino |
Canuto, Enrico | Politecnico Di Torino |
Keywords: Climate change impact and adaptation measures, Model reduction and dynamic emulation, Modeling and identification of environmental systems
Abstract: The paper has been suggested by a pair of observations: 1) the atmospheric growth rate of carbon dioxide is smaller than that ascribed to the emission by fossil fuel combustion; 2) the fossil-fuel reserves are finite. The first observation leads to a simple dynamic model, based on the balance between the land-ocean absorption and the anthropogenic emissions of CO2, only limited by the depletion of fossil-fuel reserves. The second observation suggests of projecting the historical CO2 emissions in the future, by constraining them to the limit of reserve availability. Similar projections are available in the literature, but either driven by heuristics or by complex simulation packages. Here, we provide a transparent and formal method only driven by historical data, their uncertainty and simple models. The method is proven capable of providing emission and concentration projections, which being constrained by finite reserves, may be taken as realistic bounds to forecasting exercises. The dynamics of the land-ocean absorption is proved by simplifying a more complex set of equations describing the CO2 exchange between Earth’s reservoirs. The contribution of other greenhouse gases like methane and nitrous oxide has been neglected, as their emissions cannot be projected with the paper method. Notwithstanding this limitation, the paper results demonstrate that some of the IPCC projections are overestimated if compared to fossil-fuel physical limits, in agreement with other authors.
|
|
11:20-11:40, Paper ThA24.5 | |
Integrated Modelling Assessment of Low Carbon and Air Quality Plan Synergies (I) |
|
Arrighini, Michele | Università Di Brescia |
Zecchi, Laura | Università Di Brescia |
Volta, Marialuisa | University of Brescia |
Keywords: Integrated assessment modelling, Air quality planning and control, Model reduction and dynamic emulation
Abstract: Climate Change and Air Quality are the most crucial environmental challenges for population health and our societies. Decision makers at different scales (European, national, and regional) define low carbon and air quality plans to reduce GHG (CO2, CH4, N2O) and air pollution precursors (NOx, NMVOC, NH3, SOx, primary PM2.5) emissions. Integrated Assessment Modelling is a methodology that can support decision makers. In this paper, we formalize a decision problem based on a multi-objective approach. The solution to the problem is the efficient low carbon and air quality emission reduction measure set for the Lombardy region, one of the most polluted areas in Europe, assuming the current energy legislation in 2030.
|
|
11:40-12:00, Paper ThA24.6 | |
Surrogate Grid Model of an Atmospheric Pollutant Spread (I) |
|
Kocijan, Jus | Jozef Stefan Institute |
Hvala, Nadja | Jožef Stefan Institute |
Grašič, Boštjan | MEIS |
Mlakar, Primož | MEIS D.o.o |
Keywords: Machine learning for environmental applications, Model reduction and dynamic emulation, Modeling and identification of environmental systems
Abstract: This paper presents a method for developing computationally-efficient surrogate models for the spread of air pollution. Mitigating the pollution of Seveso-type accidents and designing evacuation scenarios require long-term prediction, which is obtained with numerical simulations of the spread of air pollution. Sophisticated simulation programs frequently possess high computational load and are not suitable for real-time computational studies and experiments. Data-driven surrogate models that are computationally fast are used for such investigations. We propose a grid of independent dynamical Gaussian-process models (GP-GIM) to simulate the spread of atmospheric pollution. This is demonstrated using a realistic example of limited complexity based on a thermal power plant in v Sov stanj, Slovenia. The results show an acceptable behaviour match between the surrogate and original models, with a tenfold decrease in computational load. This confirms the feasibility of the proposed method and makes the resulting surrogate model suitable for further experiments.
|
|
ThB02 |
Room 301 |
Advances in the Design of Cooperative Human-Machine Systems |
Invited Session |
Chair: Saito, Yuichi | University of Tsukuba |
Co-Chair: Hohmann, Soeren | KIT |
Organizer: Rothfuss, Simon | Karlsruhe Institute of Technology (KIT) |
Organizer: Hohmann, Soeren | KIT |
|
13:30-13:50, Paper ThB02.1 | |
Validation of Stochastic Optimal Control Models for Goal-Directed Human Movements on the Example of Human Driving Behavior (I) |
|
Karg, Philipp | Karlsruhe Institute of Technology (KIT) |
Stoll, Simon | Karlsruhe Institute of Technology (KIT) |
Rothfuss, Simon | Karlsruhe Institute of Technology (KIT) |
Hohmann, Soeren | KIT |
Keywords: Modeling of human performance, Identification and control methods, Human-centred automation and design
Abstract: Stochastic Optimal Control models represent the state-of-the-art in modeling goal-directed human movements. The linear-quadratic sensorimotor (LQS) model based on signal-dependent noise processes in state and output equation is the current main representative. With our newly introduced Inverse Stochastic Optimal Control algorithm building upon two bi-level optimizations, we can identify its unknown model parameters, namely cost function matrices and scaling parameters of the noise processes, for the first time. In this paper, we use this algorithm to identify the parameters of a deterministic linear-quadratic, a linear-quadratic Gaussian and a LQS model from human measurement data to compare the models' capability in describing goal-directed human movements. Human steering behavior in a simplified driving task shown to posses similar features as point-ot-point human hand reaching movements serves as our example movement. The results show that the identified LQS model outperforms the others with statistical significance. Particularly, the average human steering behavior is modeled significantly better by the LQS model. This validates the positive impact of signal-dependent noise processes on modeling human average behavior.
|
|
13:50-14:10, Paper ThB02.2 | |
A Probabilistic Dynamic Movement Primitives Framework on Human Hand Motion Prediction for an Object Transfer Scenario (I) |
|
Cai, Chen | University of Kaiserslautern |
Liu, Steven | University of Kaiserslautern Landau |
Keywords: Modeling of human performance, Security and safety of HMS, Design, modelling and analysis of HMS
Abstract: Recent advancements in Human-Robot Collaboration (HRC) have opened up promising prospects for revolutionizing the current manufacturing automation. Accurate modeling of human motion patterns is crucial for enabling the robot to understand human intention and predict their future motion based on online observations. As the widely used deterministic methods often lack confidence information about the provided result to account for the possible variability of human motion, in this work, a Probabilistic Dynamic Movement Primitives (PDMP)-based framework is adopted to recognize goal-directed human movements in the reaching phase and making online predictions. The proposed framework employs PDMP based on off-line demonstrations of relevant hand movements. To avoid frame-dependency, a novel DMP formulation with rotation and magnitude scaling is used, allowing for generalization of learned motion patterns to similar tasks. The proposed framework has been validated in experiments regarding an object transfer scenario on the workbench, using a Intel RealSense camera and OpenPose system for motion capturing. Results show that this framework can offer good performance in hand motion prediction in presence of human motion variations, and can be generalized to relevant tasks beyond the limited demonstrated trajectories.
|
|
14:10-14:30, Paper ThB02.3 | |
A Supervised Machine Learning Approach to Operator Intent Recognition for Teleoperated Mobile Robot Navigation (I) |
|
Tsagkournis, Evangelos | University of West Attica |
Panagopoulos, Dimitris | University of West Attica |
Petousakis, Giannis | Univeristy of Manchester |
Nikolaou, Grigoris | University of West Attica |
Stolkin, Rustam | University of Birmingham |
Chiou, Manolis | Extreme Robotics Lab, School of Metallurgy and Materials |
Keywords: Human operator support, Mobile robots, Telerobotics
Abstract: In applications that involve human-robot interaction (HRI), human-robot teaming (HRT), and cooperative human-machine systems, the inference of the human partner's intent is of critical importance. This paper presents a method for the inference of the human operator's navigational intent, in the context of mobile robots that provide full or partial (e.g., shared control) teleoperation. We propose the Machine Learning Operator Intent Inference (MLOII) method, which a) processes spatial data collected by the robot's sensors; b) utilizes a supervised machine learning algorithm to estimate the operator's most probable navigational goal online. The proposed method's ability to reliably and efficiently infer the intent of the human operator is experimentally evaluated in realistically simulated exploration and remote inspection scenarios. The results in terms of accuracy and uncertainty indicate that the proposed method is comparable to another state-of-the-art method found in the literature.
|
|
14:30-14:50, Paper ThB02.4 | |
Bringing a Vehicle to a Controlled Stop: Effectiveness of a Dual-Control Scheme for Identifying Driver Drowsiness and Executing Safety Control under Hands-Off Partial Driving Automation (I) |
|
Saito, Yuichi | University of Tsukuba |
Itoh, Makoto | University of Tsukuba |
Inagaki, Toshiyuki | University of Tsukuba |
Keywords: Adaptive automation, Shared control, cooperation and degree of automation, Task and functional allocation
Abstract: This study proposes a strategy to bring the vehicle to a controlled stop if the driver fails to supervise the partial driving automation. In scenarios where the driving context changes, the system provides information on the object/event detection and response, and it observes the driver’s response (i.e., pressing a button). If the driver fails to respond to the given information within 15 seconds, the system implements a first-stage control that reduces the speed to 50 km/h. If the driver does not perform the accelerator action within 30 seconds after first-stage control, the system determines that “the driver failed to supervise the partial driving automation system”. To demonstrate the effectiveness of the proposed system for identifying driver drowsiness and implementing deceleration control, a total of 26 drivers participated in an experiment. In 12 among 23 instances in which first-stage control was implemented, the system could successfully determine that “the driver failed to supervise the partial driving automation.” In 8 of the 12 instances, the vehicle was brought to a complete stop. We conclude that the system could be used effectively for safety control and for identifying the driver state.
|
|
14:50-15:10, Paper ThB02.5 | |
Model Predictive Degree of Automation Regulation for Mobile Robots Using Robot Vitals and Robot Health (I) |
|
Braun, Christian | Karlsruhe Institute of Technology |
Ramesh, Aniketh | Extreme Robotics Lab, University of Birmingham |
Rothfuss, Simon | Karlsruhe Institute of Technology (KIT) |
Chiou, Manolis | Extreme Robotics Lab, School of Metallurgy and Materials |
Stolkin, Rustam | University of Birmingham |
Hohmann, Soeren | KIT |
Keywords: Adaptive automation, Shared control, cooperation and degree of automation
Abstract: Environmental adversities can severely impact the performance of human-robot teams, potentially even leading to task failure. If the operator and the robot automation are not equally affected, adjusting the degree of automation to shift control authority between them is a means of maintaining the performance of the human-robot team. The robot vitals and robot health framework is a recent approach to quantifying runtime performance degradation in robots. This framework can serve as a methodological foundation for the adjustment of the degree of automation based on the human-robot system's state. In this paper, we contribute two model predictive adaptive automation systems that can adjust either the level or the degree of automation of a robot. These systems optimize robot health to ensure optimal performance of the human-robot team when exposed to adversities. Feasibility studies in simulation showcase the ability of our systems to manage the level and degree of automation, thus allowing for an optimal task execution by the human-robot team.
|
|
15:10-15:30, Paper ThB02.6 | |
Robotics Benchmark on Transfer Learning: A Human-Robot Collaboration Use Case |
|
Shahid, Asad Ali | Dalle Molle Institute for Artificial Intelligence, IDSIA USI-SUP |
Forgione, Marco | SUPSI-USI |
Gallieri, Marco | NNAISENSE |
Roveda, Loris | SUPSI-IDSIA |
Piga, Dario | SUPSI-USI |
Keywords: Adaptive automation, Robotics technology, Co-Learning and self-learning
Abstract: In the context of human-robot collaboration (HRC), the model of the robots needs to be adapted to describe new tasks in new environments and under new operating conditions. A long-standing challenge in HRC is to transfer the acquired robot's skills and adapt models from a limited amount of data and/or with limited computational resources. To facilitate the research addressing this issue, this paper proposes a transfer learning benchmark in a HRC setting using data acquired from a 7-DOF Franka Emika Panda robot. The goal is to estimate a dynamical model mapping set-point pose, measured pose, and velocity of the end-effector into the external interaction wrench. This type of problem may arise in real applications to design virtual sensors for forces/torques. In the proposed benchmark, the model can be estimated based on a long dataset acquired under a nominal operating condition of the robot, along with 5 shorter trajectories (to be used for model adaptation) gathered for 5 different values of translational stiffness. Performance is measured on 5 test trajectories where the same translational stiffness values of the transfer experiments are applied. Baseline results are presented using a transfer learning approach tailored to dynamical systems recently proposed in the literature.
|
|
ThB03 |
Room 302 |
Security and Privacy |
Regular Session |
Chair: Quevedo, Daniel | Queensland University of Technology (QUT) |
Co-Chair: Ahn, Hyo-Sung | Gwangju Institute of Science and Technology (GIST) |
|
13:30-13:50, Paper ThB03.1 | |
Data-Driven Cyberattack Synthesis against Network Control Systems |
|
Thapliyal, Omanshu | Hitachi America Ltd |
Hwang, Inseok | Purdue University, West Lafayette, |
Keywords: Control over networks, Decentralized and distributed control, Multi-vehicle systems
Abstract: Network Control Systems (NCSs) pose unique vulnerabilities to cyberattacks due to a heavy reliance on communication channels. These channels can be susceptible to eavesdropping, false data injection (FDI), and denial of service (DoS). As a result, smarter cyberattacks can employ a combination of techniques to cause degradation of the considered NCS performance. We consider a white-box cyberattack synthesis technique in which the attacker initially eavesdrops to gather system data, and constructs equivalent system model. We utilize the equivalent model to synthesize hybrid cyberattacks -- a combination of FDI and DoS attacks against the NCS. Reachable sets for the equivalent NCS model provide rapid, real-time directives towards selecting NCS agents to be attacked. The devised method provides a significantly more realistic approach toward cyberattack synthesis against NCSs with unknown parameters. We demonstrate the proposed method using a multi-aerial vehicle formation control scenario.
|
|
13:50-14:10, Paper ThB03.2 | |
Remote State Estimation with Privacy against Eavesdroppers |
|
Crimson, Matthew | Queensland University of Technology |
Kennedy, Justin Matthew | Queensland University of Technology |
Quevedo, Daniel | Queensland University of Technology (QUT) |
Keywords: Security in networked control systems, Remote sensor data acquisition, Estimation and filtering
Abstract: We study the problem of remote state estimation in the presence of a passive eavesdropper, under the challenging network environment of no packet receipt acknowledgments. A remote legitimate user estimates the state of a linear plant from the state information received from a sensor via an insecure and unreliable network. The transmission from the sensor may be intercepted by the eavesdropper. To maintain state confidentiality, we propose an encoding scheme. Our scheme transmits noise based on a pseudo-random indicator, pre-arranged at the legitimate user and sensor. The transmission of noise harms the eavesdropper's performance, more than that of the legitimate user. Using the proposed encoding scheme, we impair the eavesdropper’s expected estimation performance, whilst minimising expected performance degradation at the legitimate user. We explore the trade-off between state confidentiality and legitimate user performance degradation.
|
|
14:10-14:30, Paper ThB03.3 | |
Compressed Differentially Private Distributed Optimization with Linear Convergence |
|
Xie, Antai | Shanghai University |
Yi, Xinlei | KTH Royal Institute of Technology |
Wang, Xiaofan | Shanghai JiaoTong Univ |
Cao, Ming | University of Groningen |
Ren, Xiaoqiang | Shanghai University |
Keywords: Distributed optimization for large-scale systems, Security in networked control systems
Abstract: This paper addresses the problem of differentially private distributed optimization under limited communication, where each agent aims to keep their cost function private while minimizing the sum of all agents' cost functions. In response, we propose a novel Compressed differentially Private distributed Gradient Tracking algorithm (CPGT). We demonstrate that CPGT achieves linear convergence for smooth and strongly convex cost functions, even with a class of biased but contractive compressors, and achieves the same accuracy as the idealized communication algorithm. Additionally, we rigorously prove that CPGT ensures differential privacy. Simulations are provided to validate the effectiveness of the proposed algorithm.
|
|
14:30-14:50, Paper ThB03.4 | |
A Unified Approach to Differentially Private Bayes Point Estimation |
|
Lakshminarayanan, Braghadeesh | KTH Royal Institute of Technology |
Rojas, Cristian R. | KTH Royal Institute of Technology |
Keywords: Estimation theory, Statistical inference, Security and privacy
Abstract: Parameter estimation in statistics and system identification relies on data that may contain sensitive information. To protect this sensitive information, the notion of differential privacy (DP) has been proposed, which enforces confidentiality by introducing randomization in the estimates. Standard algorithms for differentially private estimation are based on adding an appropriate amount of noise to the output of a traditional point estimation method. This leads to an accuracy-privacy trade off, as adding more noise reduces the accuracy while increasing privacy. In this paper, we propose a new Unified Bayes Private Point (UBaPP) approach to Bayes point estimation of the unknown parameters of a data generating mechanism under a DP constraint, that achieves a better accuracy-privacy trade off than traditional approaches. We verify the performance of our approach on a simple numerical example.
|
|
14:50-15:10, Paper ThB03.5 | |
Inferring State-Feedback Cooperative Control of Networked Dynamical Systems |
|
Li, Yushan | Shanghai Jiaotong University |
Xu, Tao | Shanghai Jiao Tong University |
He, Jianping | Shanghai Jiao Tong University |
Chen, Cailian | Shanghai Jiao Tong University |
Guan, Xinping | Shanghai Jiao Tong University |
Keywords: Multi-agent systems, Security in networked control systems, Control of networks
Abstract: In this paper, we study the problem of inferring the state-feedback cooperative control of continuous-time NDSs from noisy state observations. To practice, we first propose a causality-based estimator to obtain the discretized system matrix, adaptive to both stable and explosive state evolution cases. Then, we derive the observation period guarantees and leverage the matrix logarithm to accurately reconstruct the continuous closed-loop matrix from the discrete one, circumventing the insufficiency of conventional sampling-recovery methods in this situation (e.g., Shannon sampling theorem). Finally, we exploit the element-wise coupling relation between the local feedback gain and the unknown interaction topology, and construct a duel-level least squares method to obtain the feedback matrix. Simulations are conducted to verify the proposed inference method.
|
|
15:10-15:30, Paper ThB03.6 | |
A Novel Security Method for Exact Average Consensus |
|
Hung, Nguyen Manh | Gwangju Institute of Science and Technology (GIST) |
Kim, Yeongung | GIST |
Ahn, Hyo-Sung | Gwangju Institute of Science and Technology (GIST) |
Keywords: Consensus, Security in networked control systems, Control of networks
Abstract: Consensus is a fundamental problem for multi-agent systems, and average consensus can be implemented for many applications, such as load balancing, and cooperative control, where all agents need to achieve an agreement using a communication network. However, the conventional approaches require information disclosure of agents to their neighbors, which is undesirable in many cases. This paper presents a novel security method for exact average consensus in a distributed manner based on the Paillier cryptosystem without a third party. To protect the privacy of an agent, we replace the initial states of this agent and one of its neighbors with virtual initial states so that the attackers can only infer the virtual initial values. Pailler cryptosystem is utilized to construct these virtual initial values, and we rigorously prove that the privacy of an agent can be guaranteed even when all of its neighbors are attackers and untrusted.
|
|
ThB04 |
Room 303 |
Wind Turbine and Wind Farm Control: Control Challenges and Solutions II |
Open Invited Session |
Chair: Mulders, Sebastiaan P. | Delft University of Technology |
Co-Chair: Pao, Lucy Y. | University of Colorado Boulder |
Organizer: van Wingerden, Jan-Willem | Delft University of Technology |
Organizer: Mulders, Sebastiaan P. | Delft University of Technology |
Organizer: Fleming, Paul | NREL |
Organizer: Schlipf, David | University of Stuttgart |
Organizer: Johnson, Kathryn | Colorado School of Mines |
Organizer: Pao, Lucy Y. | University of Colorado Boulder |
|
13:30-13:50, Paper ThB04.1 | |
Unscented Kalman Filter-Based Blade-Effective Wind Speed Estimation for a Vertical-Axis Wind Turbine (I) |
|
Brandetti, Livia | Delft University of Technology |
Liu, Yichao | Delft University of Technology |
Pamososuryo, Atindriyo Kusumo | Delft University of Technology |
Mulders, Sebastiaan | Delft University of Technology |
Watson, Simon | Delft University of Technology |
van Wingerden, Jan-Willem | Delft University of Technology |
Keywords: Modeling and simulation of power systems, Control of renewable energy resources, Control system design
Abstract: On-shore horizontal-axis wind turbines (HAWTs) provide a cost-effective solution for low-carbon electricity generation. However, public acceptance is still a problem. A possible alternative to a HAWT is a vertical-axis wind turbine (VAWT), which is more visually appealing and less noisy. Furthermore, the inherent omni-directionality of VAWTs makes them suitable for installation in urban environments where the turbulence levels are high and the wind direction variations are significant. However, the variation with the azimuth angle of the blade-effective wind speed and the angle of attack makes VAWT performance difficult to predict. This study proposes a wind speed estimator for a VAWT to address this challenge and to exploit knowledge of the blade-effective wind speed for load reduction control strategies. An Unscented Kalman Filter is used to solve the blade-effective wind speed estimation problem and is applied to a realistic 1.5 m two-bladed H-Darrieus VAWT model, for which the aerodynamic characteristics are determined using an actuator cylinder model. The system performance is evaluated using different wind speed variation scenarios. Overall, good agreement between the reference and estimated blade-effective wind speed is found both in terms of trend and absolute values.
|
|
13:50-14:10, Paper ThB04.2 | |
Wind Tunnel Testing of Combined Derating and Wake Steering by Yawing (I) |
|
Campagnolo, Filippo | Technische Universitaet Muenchen |
Tamaro, Simone | Technische Universitaet Muenchen |
Mühle, Franz | Technische Universitaet Muenchen |
Bottasso, Carlo | Technische Universität München |
Keywords: Control of renewable energy resources, Intelligent control of power systems, Optimal operation and control of power systems
Abstract: This paper describes an experimental assessment of the impact of combined derating and wake steering by yawing on the power output of a cluster of three wind turbines. The test is conducted in a boundary layer wind tunnel, and the aforementioned flow control strategies are applied to the sole upstream scaled machine. The experiment reveals a relationship, so far never observed experimentally, between the amount of yaw-induced power losses and the implemented level of derating. Furthermore, combining derating and yawing can only be beneficial, in terms of improved power production at the cluster level, for modest derating values.
|
|
14:10-14:30, Paper ThB04.3 | |
An Iterative Data-Driven Learning Algorithm for Calibration of the Internal Model in Advanced Wind Turbine Controllers (I) |
|
Mulders, Sebastiaan | Delft University of Technology |
Liu, Yichao | Delft University of Technology |
Spagnolo, Fabio | Vestas Wind Systems A/S |
Christensen, Poul Brandt | Vestas Wind Systems A/S |
van Wingerden, Jan-Willem | Delft University of Technology |
Keywords: Control of renewable energy resources, Estimation and fault detection, Machine learning methods and applications
Abstract: Modern industrial wind turbine controllers for partial-load region control are becoming increasingly complex by progressively relying on modeled aerodynamic characteristics. These advanced turbine controllers generally consist of a combined wind speed estimator and tracking controller, allowing for a granular trade-off between energy capture maximization and (fatigue) load minimization. Because of the limited measurements available to the controller, the control scheme's internal model quality is of utmost importance in satisfying performance and stability requirements. Therefore, the calibration thereof is of particular interest. To date, little work has been performed on the direct calibration of the model information. This work proposes a data-driven iterative learning algorithm for calibrating the internal physical model parameters. The learning algorithm uses generally available closed-loop turbine measurements, complemented with an external measurement of the rotor effective wind speed (REWS), and is thereby largely nondisruptive. The algorithm is based on steady-state assumptions and performs iterative batch-wise updates of the internal control model toward convergence. As the algorithm corrects at the actual turbine operating point, short-term relocations of the turbine's operating point can be used to calibrate in a broader operational domain. Results show outstanding learning capabilities for an aerodynamically degraded wind turbine under realistic turbulent wind conditions. Moreover, a sensitivity study is performed to expose the algorithm's susceptibility to measurement errors, algorithm tuning, and the size of the data set.
|
|
14:30-14:50, Paper ThB04.4 | |
Physics-Informed Data-Driven Reduced-Order Models for Dynamic Induction Control (I) |
|
Muscari, Claudia | Politecnico Di Milano, TU Delft |
Schito, Paolo | Politecnico Di Milano |
Viré, Axelle | Delft University of Technology |
Zasso, Alberto | Politecnico Di Milano |
van Wingerden, Jan-Willem | Delft University of Technology |
Keywords: Control of renewable energy resources, Modeling and simulation of power systems, Optimal operation and control of power systems
Abstract: In this work, we find a reduced-order model for the wake of a wind turbine controlled with dynamic induction control. We use a physics-informed dynamic mode decomposition algorithm to reduce the model complexity in a way such that the physics of the wake mixing can be investigated and that the model itself can be easily embedded into control-oriented frameworks. After discussing the advantage of forcing the linear system resulting from the algorithm to be conservative (as a consequence of the periodicity of the pitch excitation) and the choice of observables, we describe a procedure for calculating the energy associated with individual modes. The considered data-set is composed of large eddy simulation (LES) results for a single DTU 10 MW wind turbine in uniform flow. Simulations were performed first with baseline control (for reference) and then with the Pulse and the Helix approaches with constant excitation amplitude and different excitation frequencies. The frequencies and energies associated with the resulting modes are discussed.
|
|
14:50-15:10, Paper ThB04.5 | |
Koopman Model Predictive Control for Wind Farm Yield Optimization with Combined Thrust and Yaw Control (I) |
|
Dittmer, Antje | German Aerospace Center |
Sharan, Bindu | Hamburg University of Technology |
Werner, Herbert | Hamburg University of Technology |
Keywords: Model predictive and optimization-based control, System identification and modelling, Control of renewable energy resources
Abstract: Two novel approaches to data-based wind farm control via Koopman model predictive control are presented, both combining thrust and yaw control for yield optimization and power reference tracking. The analytical Gaussian wake model and open loop simulations in the WFSim environment are used to investigate the potential increase of farm power yield due to yaw misalignment for a two turbine configuration and a wind test case with constant wind speed and the wind direction parallel to the main axis of the farm. In closed-loop simulation, the two Koopman model predictive control designs reduce the tracking error considerably with regards to a previously published baseline controller, which used solely axial induction control. It is also demonstrated that the second, purely data-based, Koopman design, resulting in larger improvement in tracking, achieves this with smaller yaw angles, avoiding mechanical loads acting on turbines operating misaligned to the wind, making this a promising candidate for further investigation in medium and high fidelity simulation environments.
|
|
15:10-15:30, Paper ThB04.6 | |
Phase Synchronization for Helix Enhanced Wake Mixing in Downstream Wind Turbines (I) |
|
van Vondelen, Aemilius Adrianus Wilhelmus | Delft University of Technology |
Ottenheym, Joris | Delft University of Technology |
Pamososuryo, Atindriyo Kusumo | Delft University of Technology |
Navalkar, Sachin | Delft University of Technology |
van Wingerden, Jan-Willem | Delft University of Technology |
Keywords: Control system design, Intelligent control of power systems, Control of renewable energy resources
Abstract: Wind farm controllers such as the Helix approach have shown potential in increasing plant power production through wake mixing. The concept suggests that actuating the upstream turbines' blade pitching with a specific periodic signal can induce a helix-shaped wake, thereby alleviating wind velocity deficit on downstream turbines. Wake mixing initiation by downstream turbines may also be shown advantageous for power production; however, little to no attention has been given to such an approach. Similar wake mixing is expected to be achievable at lower control costs if the downstream turbine can benefit from the periodic component already present in the wake of the upstream turbine. Such a hypothesis is studied in this work by designing a minimal control scheme where the wake acting on the downstream turbine is simulated by a periodic input disturbance. A Kalman filter is proposed for incoming input disturbance phase estimation using SCADA data. The reconstructed phase information allows synchronization of the downstream control action with the periodic input disturbance by means of a phase synchronization wake mixing controller. The periodic component was estimated with a minimal root-mean-square error and the resulting control action was in phase with the input disturbance and demonstrated satisfactory performance even with a small phase perturbation. Future work will include applications in a high-fidelity wind turbine model and wind tunnel studies.
|
|
ThB05 |
Room 304 |
Predictive Control II |
Regular Session |
Chair: Johansson, Karl H. | KTH Royal Institute of Technology |
Co-Chair: Monnigmann, Martin | Ruhr-Universität Bochum |
|
13:30-13:50, Paper ThB05.1 | |
Asynchronous Computation of Tube-Based Model Predictive Control |
|
Sieber, Jerome | ETH Zurich |
Zanelli, Andrea | ETH Zurich |
Leeman, Antoine | ETH |
Bennani, Samir | European Space Agency |
Zeilinger, Melanie N. | ETH Zurich |
Keywords: Predictive control, Uncertain systems, Robust control (linear case)
Abstract: Tube-based model predictive control (MPC) methods bound deviations from a nominal trajectory due to uncertainties in order to ensure constraint satisfaction. While techniques that compute the tubes online reduce conservativeness and increase performance, they suffer from high and potentially prohibitive computational complexity. This paper presents an asynchronous computation mechanism for system level tube-MPC (SLTMPC), a recently proposed tube-based MPC method which optimizes over both the nominal trajectory and the tubes. Computations are split into a primary and a secondary process, computing the nominal trajectory and the tubes, respectively. This enables running the primary process at a high frequency and moving the computationally complex tube computations to the secondary process. We show that the secondary process can continuously update the tubes, while retaining recursive feasibility of the primary process.
|
|
13:50-14:10, Paper ThB05.2 | |
Simple Tuning of Arbitrary Controllers Using Governors |
|
Fikar, Miroslav | Slovak University of Technology in Bratislava |
Kiš, Karol | Slovak University of Technology in Bratislava |
Klauco, Martin | Slovak University of Technology in Bratislava |
Monnigmann, Martin | Ruhr-Universität Bochum |
Keywords: Predictive control, Constrained control, Controller constraints and structure
Abstract: An intuitive and straightforward mechanism for tuning arbitrary controllers is proposed. While the structure and parameters of the original controller remain unchanged, the inputs to the nominal controllers are modified such that the closed-loop response becomes slower or faster. Such a governor setup implementation is advantageous, especially when re-tuning the original controller is impractical. The applicability and versatility of this approach is presented using several examples spanning from simple loops with PID controllers to complex nonlinear closed-loop systems with optimal and approximated explicit MPC.
|
|
14:10-14:30, Paper ThB05.3 | |
Risk-Aware Stochastic Energy Management of Microgrid with Battery Storage and Renewables |
|
Ábelová, Tereza | TESLA 50Hz, S.r.o, Slovakia |
Kohút, Roman | Slovak University of Technology in Bratislava |
Fedorová, Kristína | Slovak University of Technology in Bratislava, Faculty of Chemic |
Kvasnica, Michal | Slovak University of Technology in Bratislava |
Keywords: Predictive control, Optimal operation and control of power systems, Smart grids
Abstract: This paper deals with optimization-based control of real microgrids with uncertain forecasts of renewable energy production and local consumption. To achieve maximum economic benefits, these uncertainties need to be accounted for in a systematic fashion. Conventionally, this task is approached by employing stochastic model predictive control. While doing so allows to account for uncertainties in the forecasts, the downside is high computational complexity that hinders implementation in real time. In this paper we therefore propose an alternative method that decreases the computational burden by an order of magnitude without inducing significant suboptimality. The approach is based on splitting the stochastic model predictive control problem into two stages, one that employs multiple realizations of the uncertainties combines with a low-fidelity prediction model, and one that uses only the risk-aware realization, combined with a high-fidelity model. The theoretical development is then showcased on a real microgrid to confirm viability of our approach.
|
|
14:30-14:50, Paper ThB05.4 | |
Adaptive Robust Predictive Control with Sample-Based Persistent Excitation |
|
Lu, Xiaonan | University of Oxford |
Cannon, Mark | University of Oxford |
Keywords: Predictive control, Recursive identification, Randomized algorithms
Abstract: We propose a robust adaptive Model Predictive Control strategy with online set-based estimation for constrained linear systems with unknown parameters and bounded disturbances. A sample-based test applied to predicted trajectories is used to ensure convergence of parameter estimates by enforcing a persistence of excitation condition on the closed loop system. The control law robustly satisfies constraints and has guarantees of feasibility and input-to-state stability. Convergence of parameter set estimates to the actual system parameter vector is guaranteed under conditions on reachability and tightness of disturbance bounds.
|
|
14:50-15:10, Paper ThB05.5 | |
Dual Adaptive MPC Using an Exact Set-Membership Reformulation |
|
Parsi, Anilkumar | ETH Zurich |
Liu, Diyou | ETH Zurich |
Iannelli, Andrea | University of Stuttgart |
Smith, Roy S. | Swiss Federal Institute of Technology (ETH) |
Keywords: Predictive control, Adaptive control, Robust learning systems
Abstract: Adaptive model predictive control (MPC) methods using set-membership identification to reduce parameter uncertainty are considered in this work. Strong duality is used to reformulate the set-membership equations exactly within the MPC optimization. A predicted worst-case cost is then used to enable performance-oriented exploration. The proposed approach guarantees robust constraint satisfaction and recursive feasibility. It is shown that method can be implemented using homothetic tube and flexible tube parameterizations of state tubes, and a simulation study demonstrates performance improvement over state-of-the-art controllers.
|
|
15:10-15:30, Paper ThB05.6 | |
Performance Bounds of Model Predictive Control for Unconstrained and Constrained Linear Quadratic Problems and Beyond |
|
Li, Yuchao | KTH Royal Institute of Technology |
Karapetyan, Aren | ETH Zürich |
Lygeros, John | ETH Zurich |
Johansson, Karl H. | KTH Royal Institute of Technology |
Mårtensson, Jonas | KTH Royal Institute of Technology |
Keywords: Predictive control, Optimal control theory
Abstract: We study unconstrained and constrained linear quadratic problems and investigate the suboptimality of the model predictive control (MPC) method applied to such problems. Considering MPC as an approximate scheme for solving the related fixed point equations, we derive performance bounds for the closed-loop system under MPC. Our analysis, as well as numerical examples, suggests new ways of choosing the terminal cost and terminal constraints, which are not related to the solution of the Riccati equation of the original problem. The resulting method can have a larger feasible region, and cause hardly any loss of performance in terms of the closed-loop cost over an infinite horizon.
|
|
ThB06 |
Room 311 |
Set-Valued Approaches to Control and Estimation of Uncertain Systems I |
Open Invited Session |
Chair: Dinh, Thach Ngoc | Conservatoire National Des Arts Et Métiers |
Co-Chair: Wang, Zhenhua | Harbin Institute of Technology |
Organizer: Dinh, Thach Ngoc | Conservatoire National Des Arts Et Métiers |
Organizer: Rauh, Andreas | Carl Von Ossietzky Universität Oldenburg |
Organizer: Yong, Sze Zheng | Northeastern University |
Organizer: Wang, Zhenhua | Harbin Institute of Technology |
|
13:30-13:50, Paper ThB06.1 | |
A Zonotopic Velocity Sensor Fault Detection Approach for Autonomous Underwater Vehicle (I) |
|
Li, Jitao | Harbin Engineering University |
Zhang, Yushi | Harbin Engineering University |
Yao, Feng | Harbin Engineering University |
Liu, Xing | Harbin Engineering University |
Zhang, Mingjun | Harbin Engineering University |
Wang, Zhenhua | Harbin Institute of Technology |
Wang, Xin | Heilongjiang University |
Keywords: Linear systems, Disturbance rejection (linear case), Supervision and testing
Abstract: This paper studies the problem of velocity sensor fault detection for Autonomous Underwater Vehicles. A novel fault detection method is proposed based on zonotopes. The fault is detected based on the check of the intersection between the prediction state set and the measurement state set. The performance of the proposed method is evaluated via a minimum detectable fault set. Numerical simulation is conducted to demonstrate the validity and viability of the proposed method.
|
|
13:50-14:10, Paper ThB06.2 | |
Functional Interval Observer for Discrete-Time Nonlinear Lipschitz Systems (I) |
|
Dinh, Thach Ngoc | Conservatoire National Des Arts Et Métiers |
Nguyen, Binh-Minh | The University of Tokyo |
Zhu, Fanglai | Tongji University |
Raïssi, Tarek | Conservatoire National Des Arts Et Métiers |
Keywords: Nonlinear observers and filter design, Lyapunov methods, Robust estimation
Abstract: This paper considers discrete-time nonlinear Lipschitz systems with unknown but bounded disturbances. Thanks to the existence of bounding decomposition functions for mixed monotone mappings and the Lyapunov approach, we present a functional interval observer to achieve stable upper and lower bounds for a linear function of the system state. The simulation on a numerical example is given to illustrate the theoretical results.
|
|
14:10-14:30, Paper ThB06.3 | |
Functional Interval Estimation for Continuous-Time Linear Systems (I) |
|
Ma, Youdao | Harbin Institute of Technology |
Wang, Zhenhua | Harbin Institute of Technology |
Meslem, Nacim | INP De Grenoble / CNRS |
Raïssi, Tarek | Conservatoire National Des Arts Et Métiers |
Luo, Hao | Harbin Institute of Technology |
Keywords: Robust estimation, Uncertain systems, Linear systems
Abstract: This paper presents a functional interval estimation method for continuous-time systems subject to disturbances and noise. First, a robust functional observer is synthesised to attenuate the effects of uncertainties. Then, based on interval analysis, an interval-based method is proposed to achieve tight functional interval estimation. The proposed method can provide accurate functional interval estimation results for continuous-time systems without using the stringent cooperativity condition and the traditionally required condition on the time derivative of the measurement noise. Simulation results are given to illustrate the effectiveness and superiority of the proposed method.
|
|
14:30-14:50, Paper ThB06.4 | |
LSTM-OBE Based Interval Prediction of Effluent BOD in Sewage Treatment (I) |
|
Zhou, Meng | North China University of Technology |
Zhang, Yinyue | North China University of Technology |
Wang, Jing | North China University of Technology (NCUT) |
Xue, Tonglai | North China University of Technology |
Keywords: Uncertain systems, Robust estimation, Diagnosis
Abstract: In this paper, a new interval prediction method of effluent BOD for wastewater treatment is proposed. Firstly, a point prediction method of effluent BOD based on a long short term memory (LSTM) neural network model is generated. Then, an improved LSTM-MTOBE algorithm is designed to predict the interval of effluent BOD, in which the minimum trace optimal boundary ellipsoid (MTOBE) algorithm is combined with LSTM to identify the real parameters of its output layer weights. Next, based on the properties of ellipsoids, the determination interval of the model uncertainty is obtained and analyzed. Finally, compared with some existing algorithms, the proposed method is illustrated to have better prediction accuracy and interval performance.
|
|
14:50-15:10, Paper ThB06.5 | |
Experimental Validation of an Ellipsoidal State Estimation Procedure for a Magnetic Levitation System (I) |
|
Rauh, Andreas | Carl Von Ossietzky Universität Oldenburg |
Soueidan, Jonas | ENSTA Bretagne |
Rohou, Simon | ENSTA Bretagne |
Jaulin, Luc | ENSTA Bretagne, OSM |
Keywords: Robust estimation, Uncertain systems, Nonlinear observers and filter design
Abstract: Set-based state estimation procedures have the advantage of enclosing all possible system states under the assumption of bounded measurement uncertainty, the structural correctness of dynamic systems models, and the representation of external disturbances and imperfectly known parameters by finitely large sets. In contrast to stochastic counterparts, often employing one of the available variants of Kalman filters, set-based approaches are less widely used. The reason for this observation is the fact that naive implementations often suffer from a non-negligible degree of overestimation and that (unless certain monotonicity properties are satisfied) set-based computations come with a notable increase of the computational complexity, resulting among others from required interval splitting procedures. This paper tries to resolve both issues by means of an ellipsoidal implementation of a discrete-time set-valued state estimation procedure that is validated experimentally and compared with an Unscented Kalman Filter (UKF) for a laboratory-scale magnetic levitation system.
|
|
15:10-15:30, Paper ThB06.6 | |
Distributed Interval Estimation for Continuous-Time Linear Systems: A Two-Step Method (I) |
|
Wang, Zhenhua | Harbin Institute of Technology |
Zhang, Jiahui | Harbin Institute of Technology |
Liu, Zonglin | University of Kassel |
Han, Weixin | Northwestern Polytechnical University |
Shen, Mouquan | Nanjing University of Technology, China |
Keywords: Robust estimation, Linear systems, Time-invariant systems
Abstract: This paper proposes a two-step distributed interval estimation method for continuous-time linear time-invariant (LTI) systems subject to unknown but bounded disturbance and measurement noise. First, a network of local observers is designed to obtain pointwise estimation. Second, interval estimation is obtained based on the point-wise estimation and peak-to-peak analysis. The conditions of the observer design and the peak-to-peak analysis are formulated as linear matrix inequalities, which can be solved efficiently. Compared with the distributed interval observers designed using the monotone system theory, the proposed method has less restrictive design conditions and hence broader application scopes. Moreover, the parameter matrices in the proposed method can be optimized to obtain tight interval estimation. A numerical simulation is given to illustrate the performance of the proposed method.
|
|
ThB07 |
Room 312 |
Control, Estimation, and Optimization for Networked Systems |
Regular Session |
Chair: Ye, Mengbin | Curtin University |
Co-Chair: Chanfreut, Paula | TU Eindhoven |
|
13:30-13:50, Paper ThB07.1 | |
Decentralised Adaptive-Gain Control for the SIS Network Epidemic Model |
|
Walsh, Liam | Curtin University |
Ye, Mengbin | Curtin University |
Anderson, Brian D.O. | Australian National Univ |
Sun, Zhiyong | Eindhoven University of Technology (TU/e) |
Keywords: Decentralized control and large-scale systems, Control of networks, Adaptive control of multi-agent systems
Abstract: This paper is concerned with the deterministic Susceptible-Infected-Susceptible (SIS) network for epidemic spreading, where each node of the network represents a population and directed edges represent transmission pathways for the disease to spread between populations. Motivated by the use of Non-Pharmaceutical Interventions (NPIs), e.g., physical distancing or mobility restrictions, to address outbreaks of novel infectious diseases, we propose a class of adaptive-gain controllers which are decentralised, being implemented independently at each node. The gains dynamically decrease over time and directly reduce the infection rates of the network at the node-level, representing an increase in NPIs for each population. We prove that for any SIS network, the adaptive-gain controllers asymptotically drive the network state to the disease-free state from any initial condition, and every gain is positive in the limit. We obtain upper bounds on the limiting gain values and the final reproduction number of the network, and conclude by proposing future research directions.
|
|
13:50-14:10, Paper ThB07.2 | |
Loitering Formation of Fixed-Wing UAV Swarms under Communication Delay and Switching Topology (I) |
|
V. Pham, Thiem | Viettel High Technology Industries Corporation |
Vu, V. Dung | Viettel High Technology Industries Corporation |
Nguyen, T. Dong | Viettel High Technology Industries Corporation |
Dong, N, Nhat | Viettel High Technology Industries Corporation |
Keywords: Multi-agent systems, Coordination of multiple vehicle systems, Control under communication constraints
Abstract: In this paper, we design a cooperative loitering formation guidance algorithm for the path-following formation of multiple fixed-wing UAVs. We are interested in the case of communication delays and switching topology. Our proposal has two main parts: path-following (lateral guidance) and path formation (longitudinal guidance). In particular, using a vector field approach, the former guarantees that the lateral distance between a fixed-wing UAV and its desired path converges in presence of wind disturbance. In the meantime, the latter proposes a cooperative path-following framework. We prove the convergence of the proposed method in uniform communication delays and switching topology. In addition, we give an upper bound of delays, which depends on the communication graph and a gain of a formation controller. Finally, we develop a robust hardware-in-the-loop (HIL) platform flight test to verify the feasibility of our proposed approach.
|
|
14:10-14:30, Paper ThB07.3 | |
Parallel-Priority-Based Distributed Model Predictive Control for Collision Avoidance |
|
Ichikawa, Ryoya | Meiji University |
Ichihara, Hiroyuki | Meiji University |
Keywords: Coordination of multiple vehicle systems, Distributed control and estimation
Abstract: This paper discusses a strategy of priority-based non-cooperative distributed model predictive control (PB-NC-DMPC) in a parallel manner for multi-vehicle systems with collision avoidance. The strategy of the paper gives priority to the neighbor vehicles, while higher priority vehicles have fewer constraints for avoiding collision with other vehicles. With the one- step behind state trajectories of the neighbor vehicles, each vehicle solves its DMPC problem simultaneously without any waiting time despite its priority. Furthermore, the paper employs Lagrangian relaxation to convexify the non-convex collision avoidance constraints in the MPC problem, which is equivalent to a problem of linear matrix inequalities (LMIs). Finally, the paper illustrates the effectiveness of the proposed Parallel-PB-NC-DMPC strategy through a numerical example and an experiment.
|
|
14:30-14:50, Paper ThB07.4 | |
A Coalitional MPC Approach to Control of Collaborative Vehicle Platoons |
|
Chanfreut, Paula | TU Eindhoven |
Keijzer, Twan | Delft University of Technology |
Maestre, Jose M. | University of Seville |
Ferrari, Riccardo M.G. | Delft University of Technology |
Keywords: Coordination of multiple vehicle systems, Multi-agent systems, Predictive control
Abstract: This work presents a coalitional model predictive controller for collaborative vehicle platoons. The overall system is modeled as a string of locally controlled vehicles that can share data through a wireless communication network. The vehicles can dynamically form disjoint groups that coordinate their actions, i.e., the so-called coalitions. The control goals are keeping a desired reference distance between all vehicles while allowing for occasional switching of the communication topology. Likewise, the presented controller promotes a string-stable evolution of the platoon system. Numerical results are provided to illustrate the proposed approach.
|
|
14:50-15:10, Paper ThB07.5 | |
Smart Meters Integration in Distribution System State Estimation with Collaborative Filtering and Deep Gaussian Process (I) |
|
Xu, Yifei | Tsinghua University |
Guo, Ye | Tsinghua University |
Tang, Wenjun | Tsinghua University |
Sun, Hongbin | Tsinghua University |
Li, Shiming | Guangdong Power Grid |
Dai, Yue | Guangdong Power Grid |
Keywords: Estimation and filtering, Estimation theory, Statistical inference
Abstract: The problem of state estimations for electric distribution system is considered. A collaborative filtering approach is proposed in this paper to integrate the slow time-scale smart meter measurements in the distribution system state estimation, in which the deep Gaussian process is incorporated to infer the fast time-scale pseudo measurements and avoid anomalies. Numerical tests have demonstrated the higher estimation accuracy of the proposed method.
|
|
15:10-15:30, Paper ThB07.6 | |
On Prescribed-Time Cooperative State Estimation of LTI Plants |
|
Li, Min | Inria |
Polyakov, Andrey | INRIA Lille Nord-Europe |
Zheng, Gang | INRIA Lille-Nord Europe |
Ping, Xubin | Xidian University |
Keywords: Distributed control and estimation, Consensus, Nonlinear observers and filter design
Abstract: The problem of prescribed-time cooperative state estimation is addressed in this paper. A network of strongly connected (linear homogenous) distributed observers is designed under the assumption that each observer can receive a time-varying scalar signal broadcasted by a supervisor. By properly parameter tuning, the observer gains go infinity and the estimation errors correspondingly reach zeros at the settling time prescribed by users.
|
|
ThB08 |
Room 313 |
Passivity-Based Control |
Regular Session |
Chair: Cucuzzella, Michele | University of Pavia |
Co-Chair: Naeem, Wasif | Queen's University of Belfast |
|
13:30-13:50, Paper ThB08.1 | |
A Passivity Based Approach to Predefined-Time Stabilization |
|
Singh, Bhawana | Queen's University Belfast United Kingdom |
Kamal, Shyam | Indian Institute of Technology (BHU), Varanasi |
Athanasopoulos, Nikolaos | Queen's University Belfast |
Naeem, Wasif | Queen's University of Belfast |
Keywords: Passivity-based control, Asymptotic stabilization, Stability of nonlinear systems
Abstract: Passivity theory is an efficacious framework in designing control laws, in particular, predefined-time stabilizing control laws. To that end, this paper discusses a predefined-time variant of passivity, associated Lyapunov tools, and basic analysis of this property through feedback interconnection. In particular, a series of predefined-time passivity definitions are discussed which allow to establish a relationship between the passivity framework and predefined-time stability. These definitions are exploited for designing control laws that render a passive system predefined-time stable about an equilibrium point. Moreover, several negative feedback interconnections of these systems are discussed to investigate the predefined-time passivity properties and predefined-time stability of an equilibrium point (when external inputs are zero). The efficacy of the proposed results is illustrated through academic and realistic examples, and comparison is also done with other existing methods.
|
|
13:50-14:10, Paper ThB08.2 | |
Control of Multi-Agent Systems with Distributed Delay |
|
Marton, Lorinc | Sapientia University |
Keywords: Networked systems, Passivity-based control, Nonlinear time-delay systems
Abstract: This study deals with the control of nonlinear multi-agent systems in which the interconnections among the agents can be modeled using distributed delay terms. It was shown that in the addressed multi-agent system class, the stabilization of the agent outputs can be performed with a prescribed precision. The proposed decentralized control approach combines passivity-based control, the synchronization of dynamic systems, and delay systems theory to achieve the control goal. As an application, the control of single-species migration networks with distributed delay was addressed. The setpoint control problem in such networks can be solved by extending the proposed passivity-based control with a suitably chosen feed-forward term. Simulation results are also provided to show the applicability of the proposed control strategy.
|
|
14:10-14:30, Paper ThB08.3 | |
A Generalized Approach to Impedance Control Design for Robotic Minimally Invasive Surgery |
|
Larby, Daniel Edward | University of Cambridge |
Forni, Fulvio | University of Cambridge |
Keywords: Passivity-based control, Lagrangian and Hamiltonian systems, Convex optimization
Abstract: Energy based control methods are at the core of modern robotic control algorithms. In this paper we present a general approach to virtual model/mechanism control, which is a powerful design tool to create energy based controllers. We present two novel virtual-mechanisms designed for robotic minimally invasive surgery, which control the position of a surgical instrument while passing through an incision. To these virtual mechanisms we apply the parameter tuning method of Larby and Forni (2022), which optimizes for local performance while ensuring global stability.
|
|
14:30-14:50, Paper ThB08.4 | |
On ϱ-Passivity |
|
Moreschini, Alessio | Imperial College London |
Bin, Michelangelo | University of Bologna |
Astolfi, Alessandro | Imperial Col. London & Univ. of Rome Tor Vergata |
Parisini, Thomas | Imperial College & Univ. of Trieste |
Keywords: Passivity-based control, Stability of nonlinear systems, Discrete event modeling and simulation
Abstract: We discuss passivity beyond continuous-time systems by highlighting several inconsistencies of the definition currently in use, for instance when applied to discrete-time systems, and by motivating the need for a new and more consistent notion. Hence, we propose a new definition, ϱ-passivity, that addresses the raised issues and that, as a result, is naturally applicable to a larger class of systems including discrete-time systems with non-zero relative degree. We show that, in line with the classical definition, ϱ-passivity is preserved under parallel and negative-feedback interconnection. These are preliminary results aimed at bridging passivity between different time domains, and taking the first step towards a more comprehensive and consistent passivity theory.
|
|
14:50-15:10, Paper ThB08.5 | |
Symplectic Discrete-Time Krasovskii Passivity-Based Control for Output Consensus |
|
Kawano, Yu | Hiroshima University |
Moreschini, Alessio | Imperial College London |
Cucuzzella, Michele | University of Pavia |
Keywords: Sampled-data control, Passivity-based control, Output feedback control (linear case)
Abstract: In this paper, we design a sampled-data distributed output feedback controller to achieve output consensus for linear continuous-time port-Hamiltonian systems in presence of unknown disturbances. The key idea is borrowed from Krasovskii passivity-based output consensus control for continuous-time dynamics. To conceptualise this rationale to sampled control systems, we deal with a discrete-time system arising from a symplectic discretization of a continuous-time linear port-Hamiltonian system, such as the implicit midpoint method. As a preliminary step, we introduce the concept of Krasovskii passivity for discrete-time systems and further show that a discretized linear port-Hamiltonian system is Krasovskii passive in the discrete-time sense. Then, based on the discrete-time version of Krasovskii passivity, we develop a sampled-data output feedback controller to achieve output consensus. The proposed sampled-data controller can be understood as a symplectic discretization of the continuous-time output consensus controller. Finally, we illustrate the effectiveness of the main result by achieving current sharing in a DC power network.
|
|
15:10-15:30, Paper ThB08.6 | |
Passivity of Nonlinear Time-Delay Systems |
|
Kawano, Yu | Hiroshima University |
Ahmed, Saeed | Faculty of Science and Engineering, University of Groningen |
Cucuzzella, Michele | University of Pavia |
Scherpen, Jacquelien M.A. | University of Groningen |
Keywords: Passivity-based control, Nonlinear time-delay systems, Output feedback control
Abstract: This paper presents passivity-based control of nonlinear systems with retarded delays in the state. To this end, we first show that the standard passivity concept can naturally be generalized to time-delay systems, which readily implies that a feedback interconnection (with or without communication delays) of passive time-delay systems is also passive. Then, we propose a storage functional for passivity analysis and further use it for stability analysis of controlled-passive time-delay systems. In particular, invoking an invariance principle for retarded functional differential equations, we show that a passive time-delay system can always be stabilized by a static output feedback controller under a delayed version of the zero-state detectability assumption.
|
|
ThB09 |
Room 314 |
Smart Manufacturing Via Cyber-Physical Systems |
Regular Session |
Chair: Herrera, Manuel | University of Cambridge |
Co-Chair: Yahouni, Zakaria | Univ. Grenoble Alpes, CNRS, Grenoble INP*, G-SCOP |
|
13:30-13:50, Paper ThB09.1 | |
Prediction of Power Consumption from Real Process Data of an Industrial Wood Chip Refining Plant |
|
Boffadossi, Roberto | National Research Council (CNR) |
Leonesio, Marco | National Research Council (CNR) |
Fagiano, Lorenzo | Politecnico Di Milano |
Bianchi, Giacomo | Institute of Intelligent Industrial Technologies and Systems For |
Keywords: Smart manufacturing, Sustainable Manufacturing, Closed loop identification
Abstract: Improving the efficiency of production processes is fundamental to minimize their environmental impact and energy consumption. The pulp and paper industry is a highly energy-intensive one that urgently needs to become more efficient, especially in the refining phase. In this framework, the model identification of a wood chips refining process operating in closed loop, pertaining to the production of Medium Density Fiberboard (MDF), is presented here, aimed to provide a long-term prediction of power consumption. We perform the identification via multi-batch Simulation Error Minimization (SEM), employing real process data collected on a large-scale MDF production plant during operation, without using sophisticated models or ad-hoc experimental sessions. The derived model obtains extremely high accuracy on a validation dataset while being simple enough to be used efficiently for production planning optimization. Moreover, it allows us to derive further models to predict the wear of the refiner disc, to be accounted for in a plant optimization procedure as well.
|
|
13:50-14:10, Paper ThB09.2 | |
Bipartite Networks to Enable Management of Internet Core and Metro Infrastructure |
|
Herrera, Manuel | University of Cambridge |
Sasidharan, Manu | University of Cambridge |
Indiran, Hanu Priya | University of Cambdridge |
Parlikad, Ajith Kumar | University of Cambridge |
Keywords: Intelligent maintenance systems, Graph-based methods for networked systems, Complex system management
Abstract: In Telecommunications, core and metro network infrastructure provide high-speed, low-latency internet service to national-level areas. Their optimal operation and management are essential for today's increasing internet service demand. The usual representation of such infrastructure as a complex network considers router stations and other main internet sites as network nodes, connected by links that represent fibre-optic cables. However, this representation comes with important simplifications. One of them is that two nodes are connected by one single link when in reality there are involved multiple links in that connection. This paper explores bipartite networks to model the detail of multiple links connecting two network nodes, zooming-in process. To avoid dimensional complexities, the cable disentangles will only be in place at local sub-networks where the analysis may have a particular focus of interest. For instance, this process will support the decision-making associated to re-routing operations after a traffic anomaly has been detected. To show the efficiency of this multi-resolution network approach, the paper uses the case study of the core and metro infrastructure of one of the major UK internet service providers.
|
|
14:10-14:30, Paper ThB09.3 | |
Leveraging Semantic-Based Root Cause Analysis with Alarm Flood Reduction |
|
Kottre, Andreas | Augsburg Technical University of Applied Sciences |
Schöler, Thorsten | Augsburg University of Applied Sciences |
Legat, Christoph | HEKUMA GmbH |
Keywords: Intelligent maintenance systems, Alarm analysis, Knowledge-based control
Abstract: Today’s demands on manufacturing companies, which include high production volume and quality, imply that machine downtime must be reduced as much as possible. However, since mechanical failures in complex industrial plants can never be completely avoided, it is important to support operators in finding the root cause of the failure as quickly as possible in order to restore the machine to a productive state. This can be done using root cause analysis systems. However, current approaches need to process large amounts of data to deliver a result and are difficult to adapt to different machines. This paper solves these problems by combining root cause analysis with alarm flood reduction to reduce the amount of data to be processed. It also presents a semantic model to formulate the relationships between alarm floods and root causes. In addition, a concept that ensures adaptability to different machines is presented.
|
|
14:30-14:50, Paper ThB09.4 | |
Scheduling AIV Transporter Using Simulation-Based Supervised Learning: A Case Study on a Dynamic Job-Shop with Three Workstations |
|
Hosseini, Arman | University of Grenoble Alpes |
Yahouni, Zakaria | Univ. Grenoble Alpes, CNRS, Grenoble INP*, G-SCOP |
Feizabadi, SeyedMohammadGhasem | University of Grenoble Alpes |
Keywords: Job and activity scheduling, Scheduling and optimization of transportation systems, Machine learning
Abstract: Dynamic job shop scheduling consists of scheduling jobs dynamically with different routing on a set of machines. A feasible and quick solution can be computed using heuristics. One well-known heuristic in job shop problems is selecting the priority dispatching rule (such as giving priority to the job with the Shortest Processing Time called SPT). Nowadays, with the application of industry 4.0 technologies such as sensors, Intelligent robots, etc., workshop data are more accessible and can be exploited to find the appropriate dispatching rule depending on the state of the shop. This work proposes a data-driven methodology for scheduling an AIV (Autonomous Intelligent Vehicle) that supplies three workstations. Our approach is based on data collected from an Arena simulation model fed to a supervised learning algorithm. This one helps identify one among five dispatching rules for each scheduling decision.
|
|
14:50-15:10, Paper ThB09.5 | |
EPQ Inventory Model with Backorders and Energy Implications |
|
Nguyen, Hong Nguyen | University of Technology of Troyes |
Godichaud, Matthieu | University of Technology of Troyes |
Amodeo, Lionel | University of Technology of Troyes |
Keywords: Inventory control, Operations research, Supply chain management
Abstract: With the scarcity of energy supply in the world and especially in the European region, energy price is soaring rapidly. Therefore, finding solutions to save energy is a top priority for manufacturers. This study introduces an EPQ inventory model that takes into account the correlation between production processes and energy consumption, while also allowing for backorders. The energy consumption during both production and non-production periods of the machine is computed. The energy consumption in EPQ policies is contingent upon the production rate and the machine's states (off or standby) during non-production phases. Utilizing the proposed resolution algorithm, the model under examination seeks to minimize the average total system cost while considering the production rate, cycle time, the initial production time of the cycle, and the optimal machine state during non-production periods. To demonstrate the formulated model, a numerical analysis is conducted, with a particular focus on the impact of allowing backorders.
|
|
ThB10 |
Room 315 |
Micro-Meteorology Control - towards Harmony of Environments and Human
Activities |
Open Invited Session |
Chair: Onishi, Ryo | Tokyo Institute of Technology |
Co-Chair: Nonomura, Taku | Tohoku University |
Organizer: Onishi, Ryo | Tokyo Institute of Technology |
Organizer: Nonomura, Taku | Tohoku University |
Organizer: Hara, Shinji | Tokyo Institute of Technology |
|
13:30-13:50, Paper ThB10.1 | |
Micro-Meteorology Control: Background and Technical Issues towards Harmony of Environments and Human Activities (I) |
|
Hara, Shinji | Tokyo Institute of Technology |
Onishi, Ryo | Tokyo Institute of Technology |
Nonomura, Taku | Tohoku University |
Tsubakino, Daisuke | Nagoya University |
Suzuki, Satoshi | Chiba University |
|
|
13:50-14:10, Paper ThB10.2 | |
Real-Time Harmonic Prediction of Urban Micrometeorology Based on AI-Integrated Simulation (I) |
|
Onishi, Ryo | Tokyo Institute of Technology |
Yasuda, Yuki | Tokyo Institute of Technology |
Keywords: Natural and environmental systems, Machine learning for environmental applications, Real time control of environmental systems
Abstract: Realization of real-time prediction of urban micrometeorology is a key of the future smart IoT services. For its realization, we must first solve two major bottlenecks. One is the prediction bottleneck: The micro-meteorology simulations cannot be completed in real-time, securing enough leading time. The other is the monitoring bottleneck: There is no practical means to monitor the constantly changing micro-meteorology and human activities. The two bottlenecks are to be solved simultaneously and harmonically to balance the cost and reliability for social services. Here we focus on the first bottleneck and discuss the new technology to realize urban micrometeorology simulations for a real-time purpose.
|
|
14:10-14:30, Paper ThB10.3 | |
Heuristic Actuator Selection with the Use of Data of Nonlinear Optimal Control for Fluid Flows (I) |
|
Sasaki, Yasuo | Tohoku University |
Nonomura, Taku | Tohoku University |
Keywords: Optimal control and operation of water resources systems
Abstract: In this paper, we propose a heuristic method to select actuators for optimal control based on the Navier-Stokes equations. In the proposed method, the optimal control with the use of all candidates of actuators is applied to a fluid flow in a numerical simulation, and the optimal control inputs for all the candidates are acquired. Actuators are then selected in the descending order of the norms of these optimal control inputs. This procedure is numerically tractable for some of two-dimensional and three-dimensional fluid flows. The proposed method is demonstrated for an actuator selection problem for a two-dimensional flow around a circular cylinder at Reynolds number 100. Numerical simulations reveal that actuators are selected so that the optimal controller can take the state close to the steady state with a small control effort.
|
|
14:30-14:50, Paper ThB10.4 | |
Study on Efficient Sensor Node Selection for Observability Gramian Optimization (I) |
|
Yamada, Keigo | Tohoku University |
Nagata, Takayuki | Tohoku University |
Nakai, Kumi | National Institute of Advanced Industrial Science and Technology |
Nonomura, Taku | Tohoku University |
Sasaki, Yasuo | Tohoku University |
Tsubakino, Daisuke | Nagoya University |
Keywords: Monitoring, Parameter and state estimation, Scheduling, coordination, optimization
Abstract: This study attempts a practical comparison of optimization methods for sensor node selection to efficiently monitor large-scale dynamical systems represented by linear time-invariant state space models. Sensor measurements are evaluated based on an observability measure, the matrix determinant of the observability Gramian. This study confirms the applicability of selection strategies, namely, a convex relaxation method using semidefinite programming, a greedy maximization and its approximation that considers the gradient of the observability measure. Examples based on numerical and real-world experiments illustrate the effectiveness of the selection algorithms in terms of their optimization measures and the run time for the selection.
|
|
14:50-15:10, Paper ThB10.5 | |
Accurate Wind Observation and Robust Control for Drones in the Field of Micro-Meteorology (I) |
|
Asignacion, Abner Jr | Chiba University |
Noda, Ryusuke | Tokyo University of Technology |
Nakata, Toshiyuki | Chiba University |
Tsubakino, Daisuke | Nagoya University |
Liu, Hao | Chiba University |
Suzuki, Satoshi | Chiba University |
Keywords: Modeling and identification of environmental systems
Abstract: Urban logistics has been the primary target for recent drone applications. However,these drones face varying weather conditions in their flight horizon that can limit their performance. From another perspective, this flight horizon is the focus of micro-meteorology data gathering for a city-wide accurate weather prediction system. Hence, these drones can carry out logistics while gathering micro-meteorology data. This paper focuses on the latter and aims to realize the drone capabilities required for forecasting micro-meteorology, especially observing highly accurate wind data and robust control capability against strong wind disturbances. The generation of wind maps using a 2D wind sensor mounted on a drone and wind gust estimation using a nonlinear disturbance observer (NDOB) are proposed as the capability for accurate wind observation. Next, the position and velocity control of the drone using super twisting sliding mode control (STSMC) and NDOB are designed for robust control. Lastly, numerical simulation and real-world experiments verify the effectiveness of the whole system proposed in this paper.
|
|
15:10-15:30, Paper ThB10.6 | |
Hierarchical Control and Cooperative Disturbance Estimation for Multiple Drones: Towards Application to Micro-Meteorology Control (I) |
|
Tsubakino, Daisuke | Nagoya University |
Hara, Shinji | Tokyo Institute of Technology |
Keywords: Modeling and identification of environmental systems, Multi source environmental data integration
Abstract: This paper deals with formation control and disturbance estimation problem for multiple drones in the presence of unknown disturbance forces. The unknown disturbance forces are assumed to be generated mainly by wind. In view of application to micro-meteorology control, a formation control law involving a cooperative disturbance estimation mechanism is proposed. The estimated disturbance can be used for meteorology control. The proposed control law consists of three parts: a hierarchical optimal feedback control law for translational motion, a cooperative update law for disturbance estimation, and a nonlinear attitude control law.
|
|
ThB11 |
Room 411 |
Timed and Hybrid Aspects in Discrete Event Systems I |
Invited Session |
Chair: Lefebvre, Dimitri | Univ Le Havre |
Co-Chair: Demongodin, Isabel | Aix-Marseille University |
Organizer: Lefebvre, Dimitri | Univ Le Havre |
Organizer: Demongodin, Isabel | Aix-Marseille University |
|
13:30-13:50, Paper ThB11.1 | |
Switched Max-Plus Linear-Dual Inequalities for Makespan Minimization: The Case Study of an Industrial Bakery Shop (I) |
|
Zorzenon, Davide | Technical University Berlin |
Zaiets, Nataliia | National University of Life and Environmental Sciences of Ukrain |
Raisch, Joerg | Technische Universitaet Berlin |
Keywords: Discrete event modeling and simulation, Max-plus algebra, Hybrid and switched systems modeling
Abstract: In this paper, an industrial bakery shop is modeled by switched max-plus linear-dual inequalities (SLDIs). SLDIs are timed discrete event systems suitable for describing flow shops with time-window constraints and switching operating modes, where each mode corresponds to a job type. We consider the scheduling problem of minimizing the makespan of the shop, and we show that the application of methods based on the max-plus algebra leads to a faster solution compared to standard techniques. The results of the paper are general, in the sense that they can be applied to any permutation flow shop with time-window constraints.
|
|
13:50-14:10, Paper ThB11.2 | |
On Tick Automata for Distributed Timed DESs with Synchronisations and Minimal Time Constraints (I) |
|
Komenda, Jan | Academy of Sciences of Czech Republic |
Lefebvre, Dimitri | Univ Le Havre |
Keywords: Discrete event modeling and simulation, Petri nets, Diagnosis of discrete event and hybrid systems
Abstract: This paper is about the representations of distributed timed discrete event systems (DESs) with synchronisation events and minimal time constraints. A subclass of Timed Petri nets with specific time semantics is first recalled as a reference model for the considered systems. Such a model is reformulated according to modular tick automata with minimal times that behave like logical automata. A synchronous composition of such automata is then defined and the result of this composition is a new tick automaton that has the same timed language as the original Petri net, which is not the case for the earlier model of tick automata with constant (exact) times.
|
|
14:10-14:30, Paper ThB11.3 | |
Inferring Moore Machine for Adaptive Online Hybrid Automaton Identification (I) |
|
Monier, Yan | Lurpa Ens Paris Saclay |
Faraut, Gregory | LURPA, ENS Cachan |
Denis, Bruno | ENS Paris-Saclay |
Anwer, Nabil | Université Paris-Saclay |
|
|
14:30-14:50, Paper ThB11.4 | |
Diagnosabilization of Time Petri Net for Timed Fault (I) |
|
Coquand, Camille | CNRS, LAAS, Univ De Toulouse, INSA, LAAS, F-31400 Toulouse |
Pencolé, Yannick | LAAS-CNRS, Université De Toulouse, CNRS |
Subias, Audine | LAAS-CNRS, INSA, University of Toulouse, France |
Keywords: Diagnosis of discrete event and hybrid systems, Petri nets, Discrete event modeling and simulation
Abstract: Diagnosability is the property of a system to have sufficient observable information to guarantee the diagnosis of a fault. Here, the considered fault is a timed fault, i.e. an unobservable event that occurs in bounded time since the start of the system. Starting with a system modeled as a Time Petri net that is not diagnosable, this work proposes a method that provides adjustments by restriction of static time intervals to ensure the system becomes ∆-diagnosable for that fault. These adjustments are characterized by a set of constraints over interval bounds and then provide a set of solutions, if any, to ensure the diagnosability of the system.
|
|
14:50-15:10, Paper ThB11.5 | |
The Use of Time-Interval Automata in the Modeling of Timed Discrete Event Systems and Its Application to Opacity (I) |
|
Marques, Mariana | Universidade Federal Do Rio De Janeiro |
Julio Barcelos, Raphael | UFRJ |
Basilio, Joao Carlos | Federal University of Rio De Janeiro |
Keywords: Discrete event modeling and simulation, Security in networked control systems, Diagnosis of discrete event and hybrid systems
Abstract: This paper addresses the problem of language opacity for a class of discrete-event systems whose transitions occur within some known time interval after the event becomes enabled. For this purpose, a new class of timed automata is proposed, time-interval automata (TIA), in which the time elapsed is associated with a unique clock, allowing each transition to be associated with a time interval of occurrence. We present new procedures to compute complement, projection of TIA, complete synchronous composition between TIA, which, differently from existing approaches, do not require refinement by partition. We extend the usual language-based definition of opacity to this class of timed automata, present necessary and sufficient conditions for timed language-based opacity, and propose an algorithm for its verification.
|
|
15:10-15:30, Paper ThB11.6 | |
Diagnosability of Discrete Event Systems Modeled by Time-Interval Automata (I) |
|
Viana, Gustavo | Universidade Federal Do Rio De Janeiro |
Rezende, Christiano Henrique | UFRJ |
Basilio, Joao Carlos | Federal University of Rio De Janeiro |
Keywords: Diagnosis of discrete event and hybrid systems
Abstract: We address, in this paper, the problem of diagnosability of time-interval discrete event systems (TIDES), a class of discrete event system that has a single clock structure and whose event occurrence takes place within a time interval after the previous event occurrence. The idea behind the diagnosability of TIDES is to leverage time information to distinguish faulty traces from non-faulty ones, increasing the accuracy of the fault diagnosis system. For this purpose, we use a recently proposed timed model called time-interval automaton (TIA), and, based on this model, we present necessary and sufficient conditions for diagnosability of discrete event systems modeled by TIA and an algorithm for its verification. Examples illustrate all of the results present in the paper.
|
|
ThB12 |
Room 412 |
Advanced Control Technologies for Carbon Neutrality and Intelligent
Mobility II |
Invited Session |
Chair: Nakada, Hayato | Hino Motors, Ltd |
Co-Chair: Suzuki, Tatsuya | Nagoya Univ |
Organizer: Yasui, Yuji | Honda R&D Co., Ltd. Japan |
Organizer: Kako, Junichi | Toyota Motor Corporation |
Organizer: Nakada, Hayato | Hino Motors, Ltd |
Organizer: Suzuki, Tatsuya | Nagoya Univ |
Organizer: Shen, Tielong | Sophia University |
|
13:30-13:50, Paper ThB12.1 | |
Lateral Model Predictive Control for Autonomous Vehicle Prototypes (I) |
|
Wenzel, Raphael | Honda Research Institute Europe GmbH |
Steinhardt, Nico Andreas | Honda Research Institute Europe GmbH |
Amann, Markus | Honda Research Institute Europe GmbH |
Probst, Malte | Honda Research Institute Europe GmbH |
Keywords: Trajectory tracking and path following, Autonomous vehicles, Motion control
Abstract: This paper shows a (lateral) Model Predictive Control (MPC) implementation on an Autonomous Driving (AD) prototype. Rapid prototyping and testing of AD functions in a realistic environment is a crucial step to understanding the advantages and shortcomings of algorithms in research and development of AD. Prototype vehicles show a specific set of requirements which differ from the control deployed in the final products. Such vehicles are potentially equipped with steering and pedal actuation, as well as high-precision localization systems. The control system is used for lateral trajectory control – it expects desired trajectory commands from a high-level motion planner. Building a precise prototype vehicle trajectory control has high challenges due to actuation lag and velocity-dependent vehicle dynamics, making MPC especially suited for such applications. The dynamic models used in this controller allow for simple identification and parametrization by conducting basic driving maneuvers and applying a series of commands to the actuators while recording the vehicle’s reactions with a reference measurement system. As these dynamic effects are heavily velocity-dependent, the model linearizes its internal equations at the expected velocity, which is part of the trajectory command. This enables a wide velocity range of control, reaching from standstill to about 70 km/h. In this paper, we will present both the model and architecture of the lateral control as well as the identification steps necessary to deploy it.
|
|
13:50-14:10, Paper ThB12.2 | |
Collision Avoidance in Urban Areas Using Multi-Objective Reinforcement Learning (I) |
|
Tamura, Akinori | Chiba University |
Arai, Sachiyo | Chiba University |
Keywords: Autonomous vehicles, Learning and adaptation in autonomous vehicles
Abstract: Autonomous driving is expected to reduce the number of traffic accidents caused by human error by supporting the process of recognition, decision-making, and operation of inexperienced drivers, such as the elderly and novice drivers. However, it has only been effective in situations where it is easy for drivers to make decisions, such as driving on highways. In this paper, we focus on safe and efficient autonomous driving in situations where multiple moving obstacles simultaneously exist. Model-based control is challenging because constructing a driving environment model for such situations is difficult. Therefore, we introduced a reinforcement learning technique that does not require a driving environment model. This paper proposes a collision-avoidance problem as a multi-objective sequential decision-making problem. We propose a method for learning Pareto-optimal driving policies concerning safety and speed using the multi-objective reinforcement learning algorithm, Pareto-DQN. The proposed method's performance through computer experiments is verified in a T-intersection environment. We confirmed the acquisition of multiple Pareto-optimal driving policies that could not be achieved using conventional methods with linear scalarization. The proposed method is helpful for the system designer because the more Pareto-optimal the driving policies, the more detailed the driver's preferences.
|
|
14:10-14:30, Paper ThB12.3 | |
Detection of Emergency Maneuver Scenarios for Automated Vehicles Using Deep Reinforcement Learning (I) |
|
Kunieda, Takeshi | Chiba University |
Imamura, Rintaro | Chiba University |
Arai, Sachiyo | Chiba University |
Keywords: Autonomous vehicles, Learning and adaptation in autonomous vehicles
Abstract: Recent developments in autonomous vehicle engineering have enabled superior decision-making and driving assistance. However, most accidents involving autonomous driving occurr outside the limitations of designed systems. Hence, future systems are required to be able to identify emergent situations to avoid collisions. However, situations that lead to road accidents are difficult to define. Furthermore, mistimed interventions may cause stress to the driver, or worse, increase casualties. In this context, this paper investigates the Markovian property of deep reinforcement learning to identify the states that lead to collisions, and uses the data to define emergent situations and provide a basis for evasion strategies.
|
|
14:30-14:50, Paper ThB12.4 | |
Lateral Misalignment and Yaw Angle Control Considering Vehicle Dynamics Based on Receiving Energy in Dynamic Wireless Power Transfer (I) |
|
Koishi, Tomoaki | The University of Tokyo |
Nguyen, Binh-Minh | The University of Tokyo |
Shimizu, Osamu | The University of Tokyo |
Yamada, Shota | The University of Tokyo |
Fujimoto, Hiroshi | The University of Tokyo |
Keywords: Positioning systems, Energy control in transportation, Motion control
Abstract: Recently, dynamic wireless power transfer (DWPT) has been shown to be a promising technology for the widespread of electric vehicles (EVs). To utilize this technology, a critical challenge is to eliminate the coil misalignments, which cause a decrease in the coupling coefficient, thereby considerably degrading the power transfer efficiency. Considering the rectangular coils, this paper presents a new method to estimate and eliminate lateral misalignments. Based on the dynamics model of the vehicle, the lateral misalignment is estimated by the fusion of the DWPT current and the onboard inertial measurement unit. On the other hand, the misalignment and the yaw angle of the vehicle are simultaneously controlled by using rear in-wheel motors and the front active steering system. The effectiveness of the proposed method has been demonstrated by both simulations and experiments using a vehicle developed by our research group.
|
|
14:50-15:10, Paper ThB12.5 | |
An Experimental Comparison of Physics-Based and Machine-Learning-Based Electric Vehicle Energy Consumption Estimation Methods (I) |
|
Shen, Heran | The University of Texas at Austin |
Zhou, Xingyu | University of Texas at Austin |
Yu, Anthony | University of Texas at Austin |
Maxavier, Lamantia | Tennessee Technological University |
Chen, Pingen | Tennessee Technological University |
Wang, Junmin | University of Texas at Austin |
Keywords: Automotive system identification and modelling, Electric and solar vehicles, Vehicle dynamic systems
Abstract: Electric vehicles (EVs) have gained attention in recent years due to their environmental friendliness and higher fuel efficiency. However, EV users may have concerns about their driving range. To alleviate such an anxiety, a pre-trip estimation of EV energy consumption can be helpful. There are two main approaches to predicting EV energy consumption: traditional model-based methods that use physical knowledge, and data-driven techniques that rely on machine learning methods. Although both types of methods show promise, little attention has been paid to experimentally compare their performance differences. To bridge this gap, this paper presents an experimental comparison study of three model-based and data-driven EV energy consumption estimation algorithms. Notably, real-world EV road-test datasets from urban driving are used for the comparative evaluation. Furthermore, this study offers a discussion of the pros and cons of each method, providing a guideline for algorithm improvement and selection.
|
|
15:10-15:30, Paper ThB12.6 | |
Cooperative Multi-Site EMS Sharing EV Batteries Based on Model Predictive Control (I) |
|
Shibuya, Takumi | Nagoya University |
Kuroda, Kazuhide | Nagoya University |
Inagaki, Shinkichi | Nanzan Univ |
Yamaguchi, Takuma | Nagoya University |
Suzuki, Tatsuya | Nagoya Univ |
Hirata, Kenji | University of Toyama |
Ito, Akira | Nagoya University |
Keywords: Energy control in transportation, Electric and solar vehicles, Technologies for control in transportation
Abstract: This study investigates a community energy management system (CEMS) composed of multiple individual EMSs, which minimize the cost of electricity for an entire community by sharing the onboard storage batteries of electric vehicles (EVs) among the multiple EMSs. Because EVs move between sites in the community, the EMSs need to cooperate in recharging and discharging of EV batteries with considering the movement of EVs. In this study, we propose a model predictive control of charging and discharging for EV batteries shared by multiple EMSs based on a mixed-integer quadratic programming method and a quadratic programming method. In addition, the electricity price of trade between an EV and an EMS is derived using the Lagrange multiplier in the optimization problem. Finally, the validity of the proposed system is verified using simulations.
|
|
ThB13 |
Room 413 |
Adaptive Control of Multi-Agent Systems |
Regular Session |
Chair: Chiang, Ming-Li | National Taiwan Ocean University |
Co-Chair: Guay, Martin | Queen's Univ |
|
13:30-13:50, Paper ThB13.1 | |
Adaptive Cooperative Output Regulation of General Directed Knowledge-Based Leader-Following Networks |
|
Harry, Telema | Queen's University |
Guay, Martin | Queen's Univ |
Wang, Shimin | Queen's University |
Keywords: Adaptive control of multi-agent systems, Adaptive observer design, Regulation (linear case)
Abstract: In this study, an adaptive cooperative output regulation problem is solved for a knowledge-based leader-follower heterogeneous multi-agent system over a directed communication network. Only partial information on the leader’s dynamics and output parameters is available. We use a distributed observer with an exponential convergence rate to estimate the leader’s unknown system matrix and output parameter and we design an adaptive algorithm to compute iteratively the linear matrix regulator equation online. We synthesize a state feedback controller composed of the distributed algorithm and the adaptive algorithm. Finally, through theoretical analysis and numerical example, we show that our design solves the cooperative output regulation problem with the leader’s output parameter, system matrix, and output tracking error converging to the origin exponentially.
|
|
13:50-14:10, Paper ThB13.2 | |
Adaptive Distributed Cluster Flow Control for a Group of Autonomous Robots |
|
Erofeeva, Victoria | Institute for Problems in Mechanical Engineering of the Russian |
Ershov, Vladislav | St. Petersburg State University |
Granichin, Oleg | Saint Petersburg State University |
Pankov, Vikentii | Saint Petersburg State University |
Uzhva, Denis | Saint Petersburg State University |
Granichina, Olga | St. Petersburg State University |
Keywords: Adaptive control of multi-agent systems, Distributed optimization for large-scale systems, Networked robotic systems
Abstract: Conventional multiagent control strategies rely either on pre-defined operational patterns, or complex inter-agent communications. While the former provides simple yet compelling results, the latter allows to achieve goals in complex environments with unpredictable disturbances. However, designing local networked control solutions for large-scale robotic systems is extremely challenging. A novel way to control complex systems by manipulating system clusters as sub-systems is proposed. The relation between sparsity and cluster flows is manifested in the new developed approach to estimate cluster structure of a group of robots based only on a few local observations of their states. Aiming to perform necessary measurements of all N agent states, the compressed sensing methodology is used to obtain ∼log(N) randomized aggregated measurements, followed by the corresponding series of local voting protocols for the network to reach a common aggregated state with randomized weights. Thus, the cluster control synthesis by these compressed measurements is computationally efficient, and yet precise. Effectiveness of the proposed method is illustrated in numeric simulations, where adaptive observation feedback cluster control outperforms conventional strategies.
|
|
14:10-14:30, Paper ThB13.3 | |
Distributed Adaptive Control with Momentum for Synchronization of Linear Agents |
|
Arevalo-Castiblanco, Miguel Felipe | Rice University |
Tellez-Castro, Duvan | Universidad Nacional De Colombia |
Mojica-Nava, Eduardo | Universidad Nacional De Colombia |
Keywords: Model reference adaptive control, Adaptive control of multi-agent systems, Control of networks
Abstract: This paper studies the problem of learning-based adaptive state feedback control for networks of heterogeneous agents with input and matched uncertainties. We propose a control strategy that guarantees that the closed-loop synchronization error of all agents in the network is bounded. Adaptive control laws are designed via matching conditions to approximate the dynamics of each agent, which are partially unknown. Uncertainty parameters in the model are suppressed using adaptive optimal modification theory. Moreover, a momentum-based technique is also introduced in our framework for improving the convergence behavior of the adaptive control law parameters computation. Finally, a simulation example for Cooperative Adaptive Cruise Control (CCAC) is presented to validate the effectiveness of the control scheme. Numerical examples show that momentum-based techniques reach the bounded error set faster than gradient-based techniques.
|
|
14:30-14:50, Paper ThB13.4 | |
Adaptive Observer for a Nonlinear System with Partially Unknown State Matrix and Delayed Measurements |
|
Kozachek, Olga | ITMO University |
Bobtsov, Alexey | ITMO University |
Nikolaev, Nikolay | ITMO University |
Keywords: Adaptive observer design, Nonlinear system identification, LPV system identification
Abstract: Problem of an adaptive state observer design for nonlinear system with unknown time-varying parameters and under condition of delayed measurements is considered. State observation problem was raised by many researchers (see for example Sanx et al. (2019)). In this paper the results proposed in Bobtsov et al. (2021b), Bobtsov et al. (2021a), Bobtsov et al. (2022a), Bobtsov et al. (2022b) are developed. The problem is solved under assumption that the state matrix can be represented as sum of known and unknown parts. The output vector is measured with a known constant delay. An adaptive observer which reconstructs unmeasured state and unknown time-varying parameter is proposed.
|
|
14:50-15:10, Paper ThB13.5 | |
Adaptive Observers for MIMO Discrete-Time LTI Systems |
|
Dey, Anchita | Indian Institute of Technology Delhi |
Bhasin, Shubhendu | Indian Institute of Technology Delhi |
Keywords: Adaptive observer design, Recursive identification, Linear multivariable systems
Abstract: In this paper, an adaptive observer is proposed for multi-input multi-output (MIMO) discrete-time linear time-invariant (LTI) systems. Unlike existing MIMO adaptive observer designs, the proposed approach is applicable to LTI systems in their general form. Further, the proposed method uses recursive least square (RLS) with covariance resetting for adaptation that is shown to guarantee that the estimates are bounded, irrespective of any excitation condition, even in the presence of a vanishing perturbation term in the error used for updation in RLS. Detailed analysis for convergence and boundedness has been provided along with simulation results for illustrating the performance of the developed theory.
|
|
15:10-15:30, Paper ThB13.6 | |
Adaptive Formation Control for Multiple Quadrotors with Nonlinear Uncertainties Using Lipschitz Neural Network |
|
Chen, YuWen | National Taiwan University |
Chiang, Ming-Li | National Taiwan Ocean University |
Fu, Li-Chen | National Taiwan Univ |
Keywords: Adaptive control of multi-agent systems, Coordination of multiple vehicle systems, Networked embedded control systems
Abstract: This paper proposes a new distributed formation control scheme for multiple quadrotors with uncertainties, which is more practical for real implementation. The proposed design takes into account the inherent nonlinear and coupled dynamics of quadrotor and incorporates the Lipschitz model uncertainty. The multi-quadrotor formation control system is divided into the high-level distributed formation controller for position control, and the low-level attitude controller for desired acceleration tracking. To improve the performance of the low-level system, we employ the Lipschitz neural network (LipNet) adaptation. LipNet adaptation learns the model uncertainty and provides a significant improvement in acceleration tracking by modifying the reference signal of the low-level system. Consequently, the performance of the whole system is enhanced. We provide a stability analysis of the proposed design and validate the performance by some simulation examples.
|
|
ThB14 |
Room 414 |
Fuzzy and Neural Systems Relevant to Control and Identification |
Regular Session |
Chair: Susto, Gian Antonio | University of Padova |
Co-Chair: Ruano, Antonio | Univ of Algarve |
|
13:30-13:50, Paper ThB14.1 | |
Minimizing the Operation Costs of a Smart Home Using a HEMS with a MILP-Based Model Predictive Control Approach (I) |
|
Gomes, Isaias L.R. | Faculty of Science & Technology, University of Algarve, 8005, Fa |
Ruano, Maria da Graça | University of Algarve |
Ruano, Antonio | Univ of Algarve |
Keywords: Fuzzy and neural systems relevant to control and identification, Machine learning in modelling, prediction, control and automation, Soft computing in control
Abstract: The energy management of a home nowadays is a challenging task, since it is necessary to take into account not only technical aspects, but also information regarding the purchase and sale prices of energy, in order to obtain an operation with minimum cost. Thus, it is necessary to develop advanced energy management systems, the so-called home energy management systems (HEMS). This paper presents a new HEMS with a mixed-integer linear programming (MILP)-based model predictive control (MPC) approach. This approach allows to obtain better results than an approach purely using MILP, by having access to updated information at every moment. The results of a real case study in Algarve, Portugal, show the superiority of MILP-based MPC over MILP and over experimental results.
|
|
13:50-14:10, Paper ThB14.2 | |
Physics-Informed Hybrid GRU Neural Network Models for MPC Prediction (I) |
|
Zarzycki, Krzysztof | Warsaw University of Technology |
Lawrynczuk, Maciej | Warsaw Univ of Technology |
Keywords: Machine learning in modelling, prediction, control and automation, Fuzzy and neural systems relevant to control and identification, Soft computing in control
Abstract: This work describes a novel Physics-Informed Hybrid Neural Network (PIHNN) model structure based on the Gated Recurrent Unit (GRU) neural network that combines the first principle and black-box data-driven approaches. We recommend the presented modeling method when the measurement of process variables is possible, but only in some limited neighborhood of the operating points, and the available first principle model describing the process is generally correct but not accurate. We discuss three methods of data fusion. Two of them utilize the fuzzy approach, while the third one relies on an additional neural network of the Multi-Layer Perceptron (MLP) type. The first method assumes a simplified data fusion block, while the next two use machine learning to minimize the overall model error. The efficiency of the presented approach and data fusion techniques is demonstrated for a benchmark chemical process (the pH reactor). Finally, we consider applying the PIHNN model in Model Predictive Control (MPC). It gives much better control quality than the MPC controller relying on the entirely black-box GRU model.
|
|
14:10-14:30, Paper ThB14.3 | |
Sugeno-Type Fuzzy Ontology PI Controller for Proportional Electrohydraulic System |
|
Benic, Juraj | University of Zagreb, Faculty of Mechanical Engineering and Nava |
Penđer, Antonia | Zagreb University of Applied Sciences |
Kasac, Josip | Faculty of Mechanical Engineering and Naval Architecture |
Stipančić, Tomislav | University of Zagreb, Faculty of Mechanical Engineering and Nava |
Keywords: Adaptive neural and fuzzy control, Remote and distributed control
Abstract: In this paper, an ontology representation of the Sougeno-type PI Fuzzy Logic Controller (FLC) is presented. The proposed controller is an extension of the Fuzzy Ontology Controller (FOC), where the new fuzzy annotations relevant to Sougeno-type fuzzy control are added to the ontology. The design of the fuzzy ontology is carried out in Protégé and it is hosted on a remote server in the Virtuoso database. Simulation results for the proportional electrohydraulic system are presented and compared to the PI and the SMC controller. The simulation results show that the proposed concept works, and achieves similar results to the PI controller. Experimental results are carried out on a proportional electrohydraulic system. Results show good tracking capabilities despite slow network communication between the server and experimental setup.
|
|
14:30-14:50, Paper ThB14.4 | |
Energy Demand Management in an Industrial Manufacturing Plant Using MPC and Neurofuzzy Models |
|
Gómez Jiménez, Javier | Universidad De Sevilla |
Chicaiza Salazar, William David | Universidad De Sevilla |
Escaño, Juan Manuel | Universidad De Sevilla |
Bordons, Carlos | Universidad De Sevilla |
Keywords: Fuzzy and neural systems relevant to control and identification, Real-time algorithms, scheduling, and programming, Industry 4.0
Abstract: An MPC controller is proposed to maximise the use of renewable energy in a manufacturing process. The strategy has been applied in a manufacturing system which has several machines, renewable generation resources, a combined heat and power (CHP) generator for power production, and a battery bank for energy storage. The work aims to maximise the use of renewable energy sources in this process, also taking into account the price of the electricity market, to reduce the cost. The use of neurofuzzy models for the prediction of the energy produced by renewable generators allows a dynamic prediction, using input values obtained from typical forecasting variables (wind speed, global irradiance, etc.).
|
|
14:50-15:10, Paper ThB14.5 | |
Deep Learning-Based Sequence Modeling for Advanced Process Control in Semiconductor Manufacturing (I) |
|
Filippo, Dalla Zuanna | Università Degli Studi Di Padova |
Gentner, Natalie | Infineon Technologies AG |
Susto, Gian Antonio | University of Padova |
Keywords: Industry 4.0, Reinforcement learning and deep learning in control, Fuzzy and neural systems relevant to control and identification
Abstract: Semiconductor manufacturing is one of the most data-intensive industry in manufacturing. Many so-called Advanced Process Control (APC) approaches based on data have been presented over the years to improve quality and efficiency, to reduce waste and increase energy savings. While on the one hand, intensive production lead to big data available for the development of Machine Learning-based technologies, on the other hand the high-mix production, multiple processes and machines, lead researchers and developers to deal with 'small data' scenarios; in this context domain adaptation approaches are highly relevant to enhance scalability. In this work we are extending a state-of-the-art Deep Learning architecture, called Domain Adversarial Neural Network based Alignment Model (DBAM) by considering new sequence learning layers. On real-world case study, the proposed architecture is shown to achieve higher accuracy, to allow for better management in the absence of large amounts of data and to make previously trained models reusable in similar scenarios.
|
|
15:10-15:30, Paper ThB14.6 | |
Local Stabilization for T-S Fuzzy Systems by a Sensor Fault Compensation Mechanism |
|
Wu, Yue | The School of Electrical Engineering, Southwest Jiaotong Univers |
Huang, Deqing | Southwest Jiaotong University |
Ma, Lei | Southwest Jiaotong University |
Keywords: Traffic control systems
Abstract: In this paper, the problem of the local stabilization for T-S fuzzy systems with sensor fault is studied. First, an unknown input observer (UIO) is designed to estimate the sensor fault of T-S fuzzy system. By virtue of the fault information provided by UIO, the scheme of local stabilization with the compensation mechanism of sensor fault is developed. Different from the conventional strategy of local stabilization, the sensor fault can be compensated in the premise part of the controller such that the design can be relaxed. Finally, the efficacy of the presented method is demonstrated by an example with respect to the system of unmanned marine vehicles.
|
|
ThB15 |
Room 415 |
Motion Control Systems |
Regular Session |
Chair: Kawai, Fukiko | Fuji Electric Co., Ltd |
Co-Chair: Uchiyama, Naoki | Toyohashi University of Technology |
|
13:30-13:50, Paper ThB15.1 | |
Energy-Optimal Coverage Motion Trajectory Generation for Industrial Machines |
|
Halinga, Mathias Sebastian | Toyohashi University of Technology |
Nyobuya, Haryson Johanes | Toyohashi University of Technology |
Uchiyama, Naoki | Toyohashi University of Technology |
Keywords: System analysis and optimization, Motion control systems, Mechatronic systems
Abstract: Coverage motion of industrial machines are widely used for manufacturing tasks such as milling, polishing, laser cutting, and inspection. Motion smoothness of industrial machines under their kinematic limits are crucial in coverage motion to increase the production efficiency and accuracy. Motion trajectory optimization for typical computer numerical control (CNC) machines plays an important role in achieving smooth motion. In addition, with the current increase in energy costs and environmental concerns, there is a great need to reduce energy consumption by industrial machines which are extensively used in manufacturing industries. This study presents an energy optimization approach for coverage motion of industrial machines, which simultaneously integrates trajectory generation and geometric path optimization. The trajectory along a linear segment is described by the modified S-curve profile with harmonic motion employed for smooth jerk continuity to enhance the motion accuracy. An energy consumption model of the feed drive system is used to achieve optimal energy. A genetic algorithm is applied for the optimization. Experimental validation of the simulation results is carried out using a two-axis feed drive system. Simulation and experimental results shows that the energy saving of the feed drive system is achieved under machine kinematic limits ensuring smooth motion.
|
|
13:50-14:10, Paper ThB15.2 | |
Extremum Seeking-Based Online Identification of Spatially Cyclic Disturbances for Rotating Systems |
|
Liu, Qingquan | Harbin Institute of Technology |
Huo, Xin | Harbin Institute of Technology |
Liu, Kang-Zhi | Chiba Univ |
Chu, Minghui | Harbin Institute of Technology |
Wu, Aijing | Harbin Institute of Technology |
Keywords: Motion control systems, Extremum seeking and model free adaptive control, Identification for control
Abstract: Spatially cyclic disturbances widely exist in rotating systems. They seriously affect the position and velocity tracking accuracy of the system. The precondition of rejecting disturbances is to obtain their related information. However, such disturbances are difficult to estimate since their time periods are generally time-varying and change with the velocity. In this paper, an extremum seeking (ES) based online identification method of spatially cyclic disturbance is proposed. he construction method of performance function is put forward, where it includes a band-pass filter and a notch filter. Besides, the envelope curve is used to outline the amplitude of periodic function in real-time. Further, the extreme value analysis of the ES-based identifier is derived. This method is independent of system parameters. The simulation results validate that the spatial cycle and amplitude of such disturbance can be accurately identified online during one operation, even if the system is still in a transient state.
|
|
14:10-14:30, Paper ThB15.3 | |
Nonlinear Model-Based Control of a Pneumatically Driven Robot |
|
Hoffmann, Kathrin | University of Stuttgart |
Trapp, Christian | Festo SE & Co. KG |
Hildebrandt, Alexander | Universitaet Stuttgart |
Sawodny, Oliver | Univ of Stuttgart |
Keywords: Motion control systems, Robots manipulators
Abstract: In robotics, pneumatic drives are an interesting alternative to classic electric drives, as their physical properties enable the design of safe, lightweight and intuitively operable robots. In this work, a nonlinear model-based feedback control concept for a robot with 4 compressed-air-driven rotary joints is presented. The robot model comprising kinetics and pressure dynamics is formulated. For this drive type, significant nonlinear friction effects are present, which is known to be challenging for controller design, especially since there is no output-side measurement of the effective drive torque after subtracting friction. A control concept based on differential flatness, here with the particular case of feedback linearization, is derived, which is particularly well suited for a system with such effects. The algorithm contains both kinetics and pressure dynamics in one central controller, and its working principle and practical implications are discussed. With experimental results, the effectiveness of the trajectory tracking controller is demonstrated and insights into the components of this controller are provided.
|
|
14:30-14:50, Paper ThB15.4 | |
Observer-Based Control Design for Overhead Crane Systems |
|
Kawai, Fukiko | Fuji Electric Co., Ltd |
Bendtsen, Jan Dimon | Aalborg Univ |
Keywords: Motion control systems, Mechatronic systems
Abstract: This paper proposes an observer-based control design with Disturbance Feedback Control (DFC) for overhead crane systems. DFC is a technique to improve the disturbance rejection capabilities of existing control loops. The crane system is modelled with 3D dynamics and linearized. Payload sway angles are estimated by a Kalman Filter. A state feedback controller for setpoint tracking and a DFC for disturbance rejection are designed using Linear Matrix Inequalities. Both simulation and experimental results show that the observer-based control with DFC can estimate the sway angle and is able to attenuate disturbance inputs better than the conventional observer-based control. The proposed design can thus achieve practical angle sensor-less control with a retro-fit modification of an existing control.
|
|
14:50-15:10, Paper ThB15.5 | |
Spatio-Temporal Analysis of Overactuated Motion Systems: A Mechanical Modeling Approach |
|
Tacx, Paul | Eindhoven University of Technology |
Teurlings, Matthijs | Eindhoven University of Technology |
Habraken, Roel | Eindhoven University of Technology |
Witvoet, Gert | TNO |
Heertjes, Marcel | Eindhoven University of Technology |
Oomen, Tom | Eindhoven University of Technology |
Keywords: Mechatronic systems, Mechatronics, Motion control
Abstract: Flexible dynamics in motion systems lead to inherent spatio-temporal system behavior. The aim of this paper is to develop a unified approach for the identification of modal models of spatio-temporal overactuated systems. The approach exploits the modal modeling framework and the overactuated setting to enhance the estimation of the spatial system behavior. The proposed approach is applied in an experimental case study. The case study considers an experimental overactuated stage and illustrates the effectiveness of the proposed approach.
|
|
15:10-15:30, Paper ThB15.6 | |
Benchmark Problem for Magnetic-Head Positioning Control System in HDDs (I) |
|
Atsumi, Takenori | Chiba Institute of Technology |
Keywords: Motion control systems, Vibration control, Micro and nano mechatronic Systems
Abstract: In the ``Cloud Era'', the data capacity of the hard disk drive (HDD) must grow to develop the cloud. As a result, we must improve the positioning accuracy of the magnetic head in the HDD. To encourage research about magnetic-head positioning control, we release a benchmark problem that works on MATLAB. This benchmark problem enables us to simulate the magnetic-head positioning control system for the latest HDDs with our designed controller. In this paper, a control design method with the decoupling filter is also presented for this benchmark problem.
|
|
ThB16 |
Room 416 |
Multi-Agent Systems II |
Regular Session |
Chair: Lin, Zongli | University of Virginia |
Co-Chair: Soni, Sandeep Kumar | INSA Centre Val De Loire Campus De Bourges |
|
13:30-13:50, Paper ThB16.1 | |
Flexible Multi-Robot Formation Tracking: A Practical Evaluation on DDR’s |
|
Gonzalez Yances, Neftali Jonatán | Centro De Investigación Y Estudios Avanzados Del Instituto Polit |
Morales, America | CINVESTAV SALTILLO |
Becerra, Hector M. | Centro De Investigación En Matemáticas (CIMAT) |
Keywords: Mobile robots, Networked robotic system modeling and control, Multi-agent systems
Abstract: This paper presents a flexible multi-robot formation tracking control that considers a time-varying formation and consensus approach. The stability analysis based on the Gershgorin's circle theorem, shows that the eigenvalues of the closed loop error dynamics matrix will have negative real part despite the number of agents, the dimension of the agent's state and the connectivity between them. The implementation of the controller on differential-drive robots shows a simple and successful method to map the control input from the two dimension Cartesian space to the robot´s wheels angular velocity. The experimental results compare the controller's performance under three connectivity topology: fully connected, ring and spanning tree; the fully connected topology gives the best performance and the spanning tree the worst. Additionally, the consensus and non-consensus controller are compared, indicating that the proposed approach achieves better performance despite perturbations.
|
|
13:50-14:10, Paper ThB16.2 | |
Semi-Global Weighted Output Average Tracking of Discrete-Time Heterogeneous Multi-Agent Systems Subject to Input Saturation and External Disturbances |
|
Song, Qilin | Shanghai Jiao Tong University |
Li, Yuanlong | Shanghai Jiao Tong University |
Xie, Yijing | University of Texas at Arlington |
Lin, Zongli | University of Virginia |
Keywords: Multi-agent systems, Systems with saturation, Tracking
Abstract: In this paper, we revisit the semi-global weighted output average tracking problem for a discrete-time multi-agent system subject to input saturation and external disturbances. The multi-agent system consists of multiple heterogeneous linear systems as leader agents and multiple heterogeneous linear systems as follower agents. A distributed state observer is designed for each follower agent that estimates the state of each leader agent. With these estimates, we design low-gain-based distributed control protocols. It is shown that, for any bounded set of the initial conditions, these control protocols cause the follower agents to track the weighted average of the outputs of the leader agents as long as the value of the low gain parameter is tuned sufficiently small. Simulation results illustrate the validity of the theoretical results.
|
|
14:10-14:30, Paper ThB16.3 | |
Bearing-Only Formation Maneuvering Control of Multi-Agent Systems with Time-Varying Leaders' Velocity |
|
Jin, Shihao | Peking University |
Guan, Jinting | Xiamen University |
Lan, Weiyao | Xiamen University |
Yu, Xiao | Xiamen University |
Keywords: Multi-agent systems, Networked robotic systems, Nonlinear cooperative control
Abstract: This paper studies bearing-only formation maneuver control of multi-agent systems modeled as double-integrators. The developed distributed control makes the multi-agent system form a desired geometric pattern in which the target formation is bearing-constrained. The controlled agents are supposed to sense the bearing and bearing rate with respect to several neighboring agents, and the interaction among agents is characterized by a fixed undirected graph. Different from existing control approaches where the target formation or the leaders move at a constant velocity, this paper investigates the case where the leaders' velocity is time-varying. For each follower agent, a finite-time velocity estimator is used to estimate its desired velocity. Then, a bearing-only control law is designed for the follower using a signum function, which renders the tracking error with respect to the leaders with time-varying velocity to converge to zero. The effectiveness of the control laws is illustrated by simulations.
|
|
14:30-14:50, Paper ThB16.4 | |
Robust Performance Analysis for Time-Varying Multi-Agent Systems with Stochastic Packet Loss |
|
Hespe, Christian | Hamburg University of Technology |
Werner, Herbert | Hamburg University of Technology |
Keywords: Multi-agent systems, Time-varying systems, Control over networks
Abstract: Recently, a scalable approach to system analysis and controller synthesis for homogeneous multi-agent systems with Bernoulli distributed packet loss has been proposed. As a key result of that line of work, it was shown how to obtain upper bounds on the H 2-norm that are robust with respect to uncertain interconnection topologies. The main contribution of the current paper is to show that the same upper bounds hold not only for uncertain but also time-varying topologies that are superimposed on the stochastic packet loss. Because the results are formulated in terms of linear matrix inequalities that are independent of the number of agents, multi-agent systems of any size can be analysed efficiently. The applicability of the approach is demonstrated on a numerical first-order consensus example, on which the obtained upper bounds are compared to estimates from Monte-Carlo simulations.
|
|
14:50-15:10, Paper ThB16.5 | |
Predefined-Time Leader-Following Formation Control of Nonlinear Multiagent Systems under Switching Topologies |
|
Soni, Sandeep Kumar | INSA Centre Val De Loire Campus De Bourges |
Boutat, Driss | INSA CVL |
Djemai, Mohamed | UVHC |
Olaru, Sorin | CentraleSupelec |
Wang, Siyuan | INSA Centre Val De Loire Campus De Bourges |
Geha, Daniel | Industrial Automation Robotics, JBI |
Soni, Garima | BIT Raipur |
Keywords: Multi-agent systems, Sliding mode control, Distributed control and estimation
Abstract: The paper proposes a predefined-time leader-following formation control scheme for nonlinear multi-agent systems with external perturbations under switching topologies. Unlike previous work on predefined-time containment control, we aim to create an isosceles triangle shaped formation instead of being covered by a generic convex hull by having followers follow the leader’s trajectories. To ensure convergence along the sliding surface within a predefined-time, we present a nonlinear sliding surface. A terminal sliding mode controller is then used to obtain the desired formation within a predefined-time. The convergence time is independent of both initial values and control parameters. Using, common Lyapunov function, predefined-time stability of closed-loop system is investigated. Simulation examples demonstrate that the developed control protocol is feasible and robust.
|
|
15:10-15:30, Paper ThB16.6 | |
Bearing-Based Target Entrapping Control of Multiple Uncertain Agents with Arbitrary Maneuvers |
|
Su, Haifan | Shanghai Jiao Tong University |
Yang, Ziwen | Shanghai Jiao Tong University |
Zhu, Shanying | Shanghai Jiao Tong University |
Chen, Cailian | Shanghai Jiao Tong University |
Yu, Wenbin | Shanghai Jiao Tong University |
Keywords: Multi-agent systems, Distributed control and estimation, Asymptotic stabilization
Abstract: This paper is concerned with bearing-based cooperative target entrapping control of multiple uncertain agents with arbitrary maneuvers including shape deformation, rotations, scalings, etc. A leader-follower structure is used, where the leaders move with the predesigned trajectories, and the followers are steered by an estimation-based control method, integrating a distance estimator using bearing measurements and a stress matrix-based formation controller. The signum functions are used to compensate for the uncertainties so that the agents' accelerations can be piecewise continuous and bounded to track the desired dynamics. With proper design of the leaders' trajectories and a geometric configuration, an affine matrix is determined so that the inter-agent relative bearings can be persistently exciting since the bearing rates are related to different weighted combinations of the affine matrix vectors. The asymptotic convergence of the estimation and control error is proved using Filipov properties and cascaded system theories. A sufficient condition for inter-agent collision avoidance is also proposed. Finally, simulation results are given to validate the effectiveness of the method.
|
|
ThB17 |
Room 417 |
Control Software Architecture |
Regular Session |
Chair: Vogel-Heuser, Birgit | Technical University of Munich |
Co-Chair: Chetto, Maryline | Nantes University |
|
13:30-13:50, Paper ThB17.1 | |
CoGoV: A Safe Motion Planning Distributed Supervision Framework for Multi-Vehicle Formations |
|
Casavola, Alessandro | Universita' Della Calabria |
D'Angelo, Vincenzo | University of Calabria |
El Qemmah, Ayman | Università Della Calabria |
Tedesco, Francesco | Università Degli Studi Della Calabria |
Torchiaro, Franco Angelo | University of Calabria |
Keywords: Control software architecture, Decentralized and distributed control, Coordination of multiple vehicle systems
Abstract: This paper introduces CoGoV: a new textit{Matlab}-based toolbox for the simulation of Command Governor supervision strategies applied to distributed motion planning problems for multi-vehicle systems. CoGoV is an open-source and object-oriented software and contains several classes for modeling unmanned vehicles, designing control strategies and solving optimization problems for achieving prescribed tasks in complex simulation scenarios. Because of its modular structure, it can be used to supervise many kinds of autonomous vehicles in marine, terrestrial and aerial domains. Throughout the paper, the benefits of the toolbox are presented by means of simulations involving the supervision and coordination of autonomous marine surface vehicles. The CoGoV toolbox is available at https://github.com/vinz-uts/CoGoV/
|
|
13:50-14:10, Paper ThB17.2 | |
Low-Cost Vision-Based Embedded Control of a 2DOF Robotic Manipulator |
|
Juchem, Jasper | Ghent University |
De Roeck, Michiel | Universiteit Gent |
Loccufier, Mia | Ghent Univ |
Keywords: Embedded computer control systems and applications, Mechatronics, Real-time algorithms, scheduling, and programming
Abstract: Simulations are frequently used to validate underactuated control of the planar two-link manipulator, a typical benchmark system. These new control strategies need to be evaluated on a mechanical setup in order to further research their validity. In this work the benchmark system is specifically designed and built to fit on a table and to be as low-cost as possible. One of the large discrepancies between the simulator and the real setup is the presence of friction. With the help of a carefully designed bearing topology and by using image vision to measure the states of the system, as opposed to mechanical sensors, this friction can be kept to a minimum. The image vision requires a computer that is capable to process the images and send the control effort to the actuator in a timely manner. For this purpose a Raspberry Pi 4 is used to interface with the camera. The architecture consists of a traditional Raspbian operating system, which is expanded with Robot Operating System (ROS) and Xenomai. With the latter, tasks can be done in hard real-time, which is needed to achieve a fixed sampling time. In this case, a sampling time of 9ms is reached. An open-loop and closed-loop experiment with PD-controller are performed to validate the software architecture.
|
|
14:10-14:30, Paper ThB17.3 | |
Real-Time Scheduling and Resource Management for Energy Autonomous Sensors |
|
Mohamed Abdulla, Mohamed Irfanulla | Nantes Universite, Ecole Centrale Nantes, CNRS, LS2N, UMR 6004 F |
Chetto, Maryline | Unviversity of Nantes |
Queudet, Audrey | Nantes Université, LS2N UMR 6004 |
Keywords: Real-time algorithms, scheduling, and programming, Embedded computer control systems and applications, Embedded robotics
Abstract: Energy autonomous sensors are attracting increasing attention because they have potential to provide monitoring for long-time and continuous measurement in many application areas such as transport and health. Energy harvesting can guarantee energy autonomy also called energy neutrality over long period of time if adequate power management strategies are implemented in sensors. As most of them have to execute multiple time critical tasks which access to shared resources in mutual exclusion, classical scheduling strategies should be revisited to provide efficient energy aware solutions. The ED-H scheduler was proved optimal to guarantee energy neutrality of uniprocessor real-time energy harvesting systems when all the tasks are assumed independent. In this paper, we propose to refine it and we introduce a new scheduling scheme, namely ED-H/DPCP which is adapted to DPCP, the well-known Dynamic Priority Ceiling Protocol to support resource access control. The paper provides the schedulability analysis attached to ED-H/DPCP. We also discuss the implementation and we present integration of ED-H/DPCP within a cobotic application.
|
|
14:30-14:50, Paper ThB17.4 | |
Trusted Execution of Periodic Tasks for Embedded Systems |
|
Gunnarsson, Martin | RISE, Research Institutes of Sweden AB |
Vreman, Nils | Lund University |
Maggio, Martina | Lund University |
Keywords: Embedded computer architectures
Abstract: Systems that interact with the environment around them generally run some periodic tasks. This class of systems include, among others, embedded control systems. Embedded controllers have been proven vulnerable to various security attacks, including attacks that alter sensor and actuator data and attacks that disrupt the calculation of the control signals. In this paper, we propose, and implement, a mechanism to execute a periodic task and its communication interfaces in a trusted execution environment. This allows us to execute an isolated controller, thus offering higher security guarantees. We analyse the overhead of switching between the regular (possibly compromised) execution environment and the trusted execution environment and quantify the effect of this defence mechanism on the control performance.
|
|
14:50-15:10, Paper ThB17.5 | |
How to Provide Fault-Tolerance Capabilities to Energy-Autonomous Sensor Systems with Real-Time Constraints? |
|
Chetto, Maryline | CAPACITES |
El Osta, Rola | Lebanese University |
Keywords: Real-time algorithms, scheduling, and programming, Fault-tolerant
Abstract: A classical real-time applicative software consists of periodic tasks which have regular arrival times and strict deadlines by which they must complete execution in all circumstances. Nonetheless, faults may be present in software, the electrical power supply may be depleted and the processor may be overloaded transiently. All these situations result in deadline missing for the tasks, which is non acceptable in hard real-time applications. The Deadline Mechanism has been introduced to cope with this issue through software redundancy. A task has two software versions, namely the primary which produces the best quality result and the backup which guarantees a result with a just acceptable precision. The aim of the paper is to show how to optimally implement the Deadline Mechanism in an autonomous sensor that should adopt an energy neutral mode for perpetual operation. In other terms, the sensor has to satisfy all deadlines despite fluctuations of energy availability and presence of software faults even if under a degraded operational mode.
|
|
15:10-15:30, Paper ThB17.6 | |
Execution Time Measurement of Narma-L2 Neural Controller Training on Embedded Devices for Mobile Machines |
|
Krüger, Marius | Technical University of Munich |
Vogel-Heuser, Birgit | Technical University of Munich |
Schwarz, Johannes | Technical University of Munich |
Kreutmayr, Fabian | HAWE Hydraulik SE |
Hujo, Dominik | Technical University of Munich |
Huber, Christoph | Technical University Munich |
Imlauer, Markus | HAWE Hydraulik SE |
Lohmann, Boris | Technische Universität München |
Keywords: Embedded computer control systems and applications, Identification and control methods, Mechatronics for mobility systems
Abstract: Many machines in the construction domain are driven by hydraulic actuators. The control of these hydraulic systems is highly challenging due to multiple nonlinearities. A promising approach for the optimal control of these hydraulic systems is adaptive control, in which the control parameters are adapted to the changing operating points. For adaptive control, the hydraulic system must be continuously identified. In this paper, an AI-based control approach (Narma-L2 Neural Controller) is presented for the hydraulic system. Based on the requirements of mobile hydraulic-driven machines, some portable heterogeneous hardware platforms are selected to measure and evaluate the execution time of computationally intensive Narma-L2 Neural Controller training. The execution time measurements enable to evaluate and assess which hardware platforms can be selected for adaptive control approaches in mobile machines to avoid overpowered hardware systems. For the demonstration proposed, four embedded single-board computers are chosen that are well established and have a similar behavior in computational power to the controllers often used in mobile systems. The execution time for Narma-L2 Neural Controller training on the most powerful considered device is more than approximately 5 times faster than on the hardware platform with the lowest computational power. The measurements presented in this paper allow to assess whether a low-cost, highly resource-limited hardware is sufficient to execute the algorithms or whether a higher-performance, but also more expensive computer should be used.
|
|
ThB18 |
Room 418 |
Kalman Filtering |
Regular Session |
Chair: Rotondo, Damiano | Universitetet I Stavanger |
Co-Chair: Boje, Edward | University of Cape Town |
|
13:30-14:10, Paper ThB18.1 | |
Revisiting State Estimation for Linear Systems with State And/or Filter Equality Constraints |
|
Chaumette, Eric | ISAE SUPAERO |
Vilà-Valls, Jordi | ISAE-SUPAERO/University of Toulouse |
Vincent, Francois | University of Toulouse / ISAE-Supaéro |
Keywords: Kalman Filtering, Estimation and filtering, Filtering and smoothing
Abstract: This article revisits optimal state estimation, in the mean squared error matrix sense, for linear systems with state and/or filter subject to linear equality constraints (LECs). First, it is shown that the conventional Wiener filter (WF) form incorporates any LECs on the state, thus yielding a filter subject to the same LECs. Conversely, an optimal linear filter subject to LECs (or linear equality gain constraints) in general does not exist. Therefore, adding LECs on the WF or WF gain matrix either leaves unchanged or degrades the constrained WF performance w.r.t. the unconstrained WF. Since the Kalman filter (KF) and Kalman predictor (KP) are recursive WF forms for linear discrete state-space (LDSS) systems, the same results hold for both estimators, which is in contradiction with several existing results in the literature. Actually, even if these existing results are mathematically correct, however, they have been derived for unsuitable assumed LDSS models where the state is surprisingly not compliant with the assumed LECs. Indeed, it is shown that for suitable assumed state models, both standard KF and KP forms satisfy the assumed LECs, making any additional projection step superfluous.
|
|
14:10-14:30, Paper ThB18.2 | |
The Weighted Kalman Filter |
|
Rotondo, Damiano | Universitetet I Stavanger |
Keywords: Kalman Filtering, Linear systems, Observers for linear systems
Abstract: This paper proposes a new version of the Kalman filter, referred to as weighted Kalman filter (WKF). In the WKF some recent results on the weighted linearization of nonlinear systems are exploited to incorporate modifications in the equations of the extended Kalman filter (EKF). More specifically, the computation of the Jacobian matrices at the current mean of the estimated state is replaced by the multiple integral over the state space of the Jacobian matrix functions multiplied by a weighting function. Similar modifications are introduced in the equations used to account for the available nonlinear model and compute the so-called a priori state and output estimates. The weighting function is chosen to be a multivariable Gaussian function where the generalized variance is selected as proportional to the current covariance matrix of the state estimate. An illustrative example is used to describe the step-by-step derivation of the WKF equations and compare its performance against the EKF in terms of convergence properties and estimation error performance.
|
|
14:30-14:50, Paper ThB18.3 | |
Fast IMU-Based Dual Estimation of Human Motion and Kinematic Parameters Via Progressive In-Network Computing |
|
Dai, Xiaobing | Technical University of Munich |
Wu, Huanzhuo | Technische Universität Dresden |
Wang, Siyi | Technical University of Munich, Chair of Information-Oriented Co |
Jiao, Junjie | Technical University of Munich |
Nguyen, Giang T. | Technical University of Dresden |
Fitzek, Frank H. P. | Technical University of Dresden |
Hirche, Sandra | Technical University of Munich |
Keywords: Kalman Filtering, Estimation and filtering, Networked robotic systems
Abstract: Many applications involve humans in the loop, where continuous and accurate human motion monitoring provides valuable information for safe and intuitive human-machine interaction. Portable devices such as inertial measurement units (IMUs) are applicable to monitor human motions, while in practice often limited computational power is available locally. The human motion in task space coordinates requires not only the human joint motion but also the nonlinear coordinate transformation depending on the parameters such as human limb length. In most applications, measuring these kinematics parameters for each individual requires undesirably high effort. Therefore, it is desirable to estimate both, the human motion and kinematic parameters from IMUs. In this work, we propose a novel computational framework for dual estimation in real-time exploiting in-network computational resources. We adopt the concept of field Kalman filtering, where the dual estimation problem is decomposed into a fast state estimation process and a computationally expensive parameter estimation process. In order to further accelerate the convergence, the parameter estimation is progressively computed on multiple networked computational nodes. The superiority of our proposed method is demonstrated by a simulation of a human arm, where the estimation accuracy is shown to converge faster than with conventional approaches.
|
|
14:50-15:10, Paper ThB18.4 | |
Accounting for Simulation Errors in Continuous-Discrete Kalman Filtering |
|
Boje, Edward | University of Cape Town |
Keywords: Kalman Filtering, Filtering and smoothing
Abstract: In continuous-discrete Kalman filter implementations there is a trade-off between the computational requirements for real time implementation, and errors incurred by selection of step size and method order in the simulation of the continuous time system model between sampling instances. Because the Kalman filter corrects errors in the state vector using output measurements, a systematic approach to account for the effects of simulation errors in the continuous-discrete Kalman filter allows the filter to be designed to deal with simulation errors in addition to conventional process (state) and measurement (output) noise.
|
|
15:10-15:30, Paper ThB18.5 | |
Adaptive Mixture Approximation for Target Tracking in Clutter |
|
D'Ortenzio, Alessandro | University of L'Aquila |
Manes, Costanzo | Università Dell'Aquila |
Orguner, Umut | Middle East Technical University |
Keywords: Kalman Filtering, Tracking, Localization
Abstract: Target tracking is a state estimation problem common in many practical scenarios like air traffic control, autonomous vehicles, marine radar surveillance and so on. In a Bayesian perspective, when phenomena like clutter are present, most existing tracking algorithms must deal with association hypotheses which may grow in number over time. In that case, the posterior state distribution can quickly become computationally intractable, and approximations must necessarily be introduced. In this work, the impact of the number of hypotheses and of reduction procedures is investigated both in terms of computational resources and tracking performances. For this purpose, a recently developed adaptive mixture model reduction algorithm is considered in order to assess its performances when applied to the problem of single object tracking in the presence of clutter and to provide some interesting insights into the addressed problem.
|
|
ThB19 |
Room 419 |
Agricultural Robotics |
Regular Session |
Chair: Paraforos, Dimitrios S. | University of Hohenheim |
Co-Chair: Chen, YangQuan | University of California, Merced |
|
13:30-13:50, Paper ThB19.1 | |
Semantic Segmentation and Inpainting of Dust with the S-Dust Dataset |
|
Buckel, Peter | DHBW Ravensburg |
Oksanen, Timo | Technical University of Munich |
Dietmüller, Thomas | DHBW Ravensburg |
Keywords: Pattern recognition and artificial intelligence in agriculture, Software sensors in agriculture, Agricultural robotics
Abstract: In agriculture the performance of camera-based vision systems is strongly affected by environmental factors, such as rain, fog, and dust. This paper presents the first open dataset for training and evaluating image processing algorithms that remove swirling dust from images. It includes images from agricultural fields during tillage, which raises dust that is manually labeled in the images. However, dust is not a classical object that can be delineated based on edges. Moreover, the dust density is not uniformly distributed but varies and is concentrated in the area behind the implement. Therefore, different segmentation approaches were investigated. First, traditional and deep-learning methods for dust segmentation in images were compared. For the neural network, a Unet with a pretrained VGG encoder was chosen. The results show that the network cannot distinguish from the background in areas with low dust density. In contrast, the traditional segmentation method based on dark channel prior (DCP) outperforms it. Subsequently, various inpainting methods to remove dust were investigated. One observation was that dust removal from images cannot be solved with current inpainting methods. The dataset is available at *.
|
|
13:50-14:10, Paper ThB19.2 | |
Communication between Agricultural Robot and Mechanical Weeding Machine Based on ISO 11783 Network |
|
Sharipov, Galibjon M. | University of Hohenheim |
Bresilla, Trim | Wageningen University and Research |
Nieuwenhuizen, Ard | Wageningen University & Research |
Hemming, Jochen | Wageningen University |
van Evert, Frits K. | Wageningen University and Research |
Aube, Christophe | AgreenCulture |
Baron, Suzanne | AgreenCulture |
Benrais, Amar | AgreenCulture |
Heiß, Andreas | University of Hohenheim |
Paraforos, Dimitrios S. | Geisenheim University |
Keywords: Precision agriculture, Standardisation in agriculture, Agricultural robotics
Abstract: Latest technologies such as advanced agriculture implements and autonomous vehicles designed with the latest sensor technologies could partially offer a solution to the challenges in agriculture that are related to crop demands, increased cost of inputs, and labor shortage. However, the compatibility, in terms of communication between the autonomous vehicle and the agricultural implements, raises the main concern. This is because most of the autonomous robotic platforms in agriculture are not compliant with existing agricultural implements that are integrated with ISO 11783 (also known as ISOBUS) standards. Besides that, there are still few agricultural processes where the implementation of ISOBUS would fulfill farmers’ needs to evaluate the performance of the implements. Weeding is one of those processes as it has a significant influence on crop growth. To address the mentioned issues, this work aims at integrating an agricultural robot with an existing mechanical weeder by leveraging ISOBUS in combination with software and hardware level. To fulfill the aim, this paper outlines the development of a middleware that makes communication between the mobile robot and the weeder possible. In addition to that, the development of an implement object pool (IOP) for the representation of the weeder performance, in terms of weeding quality, and its integration with the simulated electronic control unit (ECU) of the weeder is discussed. A preliminary analysis and assessment defined the threshold of 10% for the weeding quality that raised the STOP flag for the application.
|
|
14:10-14:30, Paper ThB19.3 | |
Long Endurance Site-Specific Management of Biochar Applications Using Unmanned Aircraft Vehicle and Unmanned Ground Vehicle |
|
An, Di | MESA Lab at UC Merced |
Krzysiak, Rafal | MESA Lab at UC Merced |
Hollenbeck, Derek | University of California Merced |
Chen, YangQuan | University of California, Merced |
Keywords: UAVs in agriculture, Agricultural robotics, Precision farming
Abstract: Agricultural activities emit an increasing amount of carbon into the atmosphere, causing climate change. Carbon sequestration is one of the carbon-neutral technologies for reducing carbon emissions by spraying biochar in the needed places. It is critical to monitor carbon emissions and the use of biochar in order to properly manage carbon emissions. Prior methods, such as traditional soil or manure sample collection and semi-automatic analysis, are expensive and time consuming, and they cannot make decisions in real time. We propose long-term, site-specific biochar application management using unmanned aircraft vehicle and unmanned ground vehicle equipped with proximity radar sensing. Our system takes the strategy that a UAV will land on a moving UGV to acquire long-range information with reliable backup. Meanwhile, the UGV has many payload options to supply the UAV's sensing and actuation missions. We evaluated our system by using a simulated mission approach that contains the analysis of the controller for the landing sequence, and real-world vision-based landing marker tracking. Results show that our system achieves robustness landing control sequence and the error altitude calculation based on computer vision is less than pm 0.02 m in average.
|
|
14:30-14:50, Paper ThB19.4 | |
Machine Vision System for Early-Stage Apple Flowers and Flower Cluster Detection for Precision Thinning and Pollination |
|
Khanal, Salik | Center for Precision and Automated Agricultural Systems, Biologi |
Bhattarai, Uddhav | Washington State University |
Sapkota, Ranjan | Center for Precision and Automated Agricultural Systems, Biologi |
Ahmed, Dawood | Center for Precision and Automated Agricultural Systems, Biologi |
Karkee, Manoj | Washington State University |
Keywords: Pattern recognition and artificial intelligence in agriculture, Agricultural robotics, Precision agriculture
Abstract: Early-stage identification of fruit’s flowers that are in both opened and unopened condition in an orchard environment is a significant information to perform crop load manage- ment operations such as flower thinning and pollination using automated and robotic platform. These operations are important in tree-fruit agriculture to enhance the fruit quality, manage crop load, and enhance the overall profit. The recent development in agricultural automation suggests that this can be done using robotics which includes machine vision technology. In this article, we proposed a vision system that detects early-stage flowers in an unstructured orchard environment using YOLOv5 object detection algorithm. For the robotics implementation, the position of a cluster of the flower blossom is important to navigate the robot and the end effector. The centroid of individual flowers (both open and unopen) was identified and associated with flower cluster via K-means clustering. The accuracy of the opened and unopened flower detection is achieved up to mAP of 81.9% in commercial orchard images.
|
|
14:50-15:10, Paper ThB19.5 | |
Feature Pyramid Network Based Proximal Vine Canopy Segmentation |
|
Molnár, Szilárd | Technical University of Cluj-Napoca |
Keresztes, Barna | Université De Bordeaux |
Tamas, Levente | Technical University of Cluj-Napoca |
Keywords: Agricultural robotics, Pattern recognition and artificial intelligence in agriculture, UAVs in agriculture
Abstract: With the widening of the Agriculture 4.0 era, the use of autonomous robots in the agriculture field is becoming a priority. The key component of such an autonomous, often multi-robot system is the perception of the environment, which is based on 2D and 3D cameras. A base processing part of the 2D images is the segmentation of different zones in the images. This is the case also in the vineyards where in order to process complex plant canopies, segmenting the parts of the image containing the area of interest is a part of the pre-processing chain. In this work, we present a Feature Pyramid Network-based grape canopy segmentation method, which has great potential to create a segmentation mask, containing only the leaves and fruits of interest. We conducted our tests in different vineyards and we also obtained the above state-of-the-art segmentation results on public and custom datasets.
|
|
15:10-15:30, Paper ThB19.6 | |
Structure Tracking Strategies in Different Agricultural Configurations |
|
Iberraken, Dimia | Université Clermont Auvergne |
Lenain, Roland | Université Clermont Auvergne, INRAE, UR TSCF, F-63000 Clermont–F |
Gaurier, Florian | Université Clermont Auvergne, INRAE, UR TSCF, F-63000 Clermont–F |
Pierre, Cyrille | Université Clermont Auvergne, INRAE, UR TSCF, F-63000 Clermont–F |
Roux, Jean-Christophe | Université Clermont Auvergne, INRAE, UR TSCF, F-63000 Clermont–F |
Keywords: Agricultural robotics, Navigation and guidance, Precision agriculture
Abstract: Navigating in an off-road environment is a challenging task. Indeed, robots need to recognize and detect significant elements on the path in order to safely navigate and perform required tasks in these environments. In this paper, it is proposed to study two different structure tracking strategies, that depend on the disposition of a 2D LiDAR perception solution that allows fulfilling different agricultural tasks. The first strategy positions the LiDAR horizontally w.r.t to the soil which permits extracting the outer contour of the structure to be followed by taking advantage of an extended vision provided by this disposition. This allows anticipation and obstacle avoidance capabilities. The second approach positions the LiDAR inclined toward the soil, allowing the recognition of the shape of a structure of interest thanks to the 3D perspective of the environment provided by the sensor layout. The 3D perspective provides knowledge on the presence or absence of vegetation. The problem associated with accurate control for mobile robots following a structure is addressed thanks to a backstepping control. In this control strategy, the longitudinal and lateral controls are computed independently and thus the regulation of the position and the orientation of the robot are separated. It is used in order to control a 4-wheel-steered mobile robot in an experimental field. The efficiency of both approaches is then investigated through full-scale experiments in various conditions.
|
|
ThB20 |
Room 421 |
Recent Trends in Modeling, Simulation and Control of Distributed Parameter
Systems II |
Open Invited Session |
Chair: Le Gorrec, Yann | FEMTO-ST, ENSMM |
Co-Chair: Ramirez, Hector | Universidad Federico Santa Maria |
Organizer: Le Gorrec, Yann | FEMTO-ST, ENSMM |
Organizer: Ramirez, Hector | Universidad Tecnica Federico Santa Maria - AC3E FB0008 |
|
13:30-13:50, Paper ThB20.1 | |
Internal Stabilization of Three Interconnected Semilinear Reaction-Diffusion PDEs with One Actuated State (I) |
|
Kitsos, Constantinos | Ecole Centrale De Nantes |
Katz, Rami | Tel Aviv University |
Fridman, Emilia | Tel-Aviv Univ |
Keywords: Control of heat and mass transfer systems, Stability of distributed parameter systems, Stability of nonlinear systems
Abstract: This work deals with the exponential stabilization of a system of three semilinear parabolic partial differential equations (PDEs), written in a strict feedforward form. The diffusion coefficients are considered distinct and the PDEs are interconnected via both a reaction matrix and a nonlinearity. Only one of the PDEs is assumed to be controlled internally, thereby leading to an underactuated system. Constructive and efficient control of such underactuated systems is a nontrivial open problem, which has been solved recently for the linear case. In this work, these results are extended to the semilinear case, which is highly challenging due the coupling introduced by the semilinearity. Modal decomposition is employed, where due to the semilinearity, the finite-dimensional part of the solution is coupled with the infinite-dimensional tail. A transformation is then employed to map the finite-dimensional part into a target system, which allows for an efficient design of a static linear proportional state-feedback controller. Furthermore, a high-gain approach is employed in order to compensate for the semilinear terms. Lyapunov stability analysis is performed, leading to LMI conditions guaranteeing exponential stability with an arbitrary decay rate. The LMIs are shown to always be feasible, provided the number of actuators and the value of the high gain parameter are large enough. Numerical examples demonstrate the proposed approach.
|
|
13:50-14:10, Paper ThB20.2 | |
Saturated Output Regulation of Distributed Parameter Systems with Collocated Actuators and Sensors (I) |
|
Govindaraj, Thavamani | Tampere University |
Paunonen, Lassi | Tampere University |
Humaloja, Jukka-Pekka | University of Alberta |
Keywords: Output regulation for distributed parameter systems, Semigroup and operator theory, Output feedback control
Abstract: This paper addresses the problem of output regulation of infinite-dimensional linear systems subject to input saturation. We focus on strongly stabilizable linear dissipative systems with collocated actuators and sensors. We generalize the output regulation theory for finite-dimensional linear systems subject to input saturation to the class of considered infinite-dimensional linear systems. The theoretic results are illustrated with an example where we consider the output regulation of a flexible satellite model that is composed of two identical flexible solar panels and a center rigid body.
|
|
14:10-14:30, Paper ThB20.3 | |
Strict Dissipativity for LQ Problem with Left-Invertible Underlying Semigroups (I) |
|
Li, Zhuqing | University of Waterloo |
Guglielmi, Roberto | University of Waterloo |
Keywords: Structural properties, Infinite-dimensional systems (linear case), Semigroup and operator theory
Abstract: The paper analyzes the strict dissipativity property of generalized linear-quadratic infinite dimensional control systems. For dynamics described by left-invertible semigroups, we first characterize exponential detectability of the system in terms of an analytic condition. Then, under a stabilizability assumption, we establish the equivalence beween strict dissipativity and exponential detectability of the system.
|
|
14:30-14:50, Paper ThB20.4 | |
Adaptive Observer Design for Heat PDEs with Discrete and Distributed Delays and Parameter Uncertainties (I) |
|
Ossama, Ammari | University Hassan II, Faculty of Science and Technology |
Giri, Fouad | University of Caen Normandie |
Krstic, Miroslav | Univ. of California at San Diego |
Chaoui, Fatima-Zahra | ENSET, Université Mohammed V |
El Majdoub, Khalid | University Hassan II, Faculty of Science and Technology, Casabla |
Keywords: Observer design, Infinite-dimensional systems (linear case), Time-delay systems
Abstract: The problem of observer design is addressed for heat partial differential equations (PDEs) that are subject to parameter uncertainties and time delays. In addition to parameter uncertainty, the novelty also lies in the presence of time-delay in the domain. Both discrete and distributed delays are accounted for and dealt with using a unified integral representation. We design an adaptive observer that provides online estimates of the states and parameters. The observer is designed using the backstepping design method involving a Volterra transformation and a state-parameter decoupling transformation. The observer stability analysis is dealt with using a Lyapunov-Krasovskii functional. It is shown, under a persistent excitation (PE) assumption, that the resulting estimation error system is exponentially stable for small delays.
|
|
14:50-15:10, Paper ThB20.5 | |
Robustly Linearized Model Predictive Control for Nonlinear Infinite-Dimensional Systems |
|
El-Kebir, Hamza | University of Illinois at Urbana-Champaign |
Berlin, Richard | University of Illinois Urbana-Champaign |
Bentsman, Joseph | Univ. of Illinois at Urbana-Champaign |
Ornik, Melkior | Univ. of Illinois at Urbana-Champaign |
Keywords: Model predictive control for distributed parameter systems, Uncertain systems, Constrained control
Abstract: This work presents a computationally efficient approach to robustly linearized model predictive control for nonlinear affine-in-control evolution equations on infinite-dimensional system state. In this setting, robust linearization refers to a need to account for the approximation errors in linearization and discretization in the model predictive control law, such that the original output constraints are not violated on the true system, a feature that present model predictive control frameworks lack. The main purpose of this work is to enable tractable model predictive control for nonlinear distributed parameter systems while accounting for these approximation errors by means of output constraints. These output constraints are derived using tight integral inequalities that rest on mild assumptions on the nonlinear system dynamics, and are easy to evaluate in real-time. Using our method, linearization and discretization errors are explicitly accounted for, producing for the first time a model predictive control law that is robust to approximation errors. This approach hence enables a trade-off between computational efficiency and strictness of output constraints, much akin to robust control methods. We demonstrate our method on a nonlinear distributed parameter system, namely a one-dimensional heat equation with a velocity-controlled moveable heat source, motivated by autonomous energy-based surgery.
|
|
15:10-15:30, Paper ThB20.6 | |
Adaptive Boundary Observer for ARZ Traffic Flow Model with Domain and Boundary Uncertainties (I) |
|
Wu, Jiahao | Beijing University of Technology |
Zhan, Jingyuan | Beijing University of Technology |
Zhang, Liguo | Beijing University of Technology |
Keywords: Observer design, Disturbance estimation and sliding mode control of distributed parameter systems, Uncertain systems
Abstract: This paper studies the problem of the adaptive boundary observer design for the Aw-Rascle-Zhang (ARZ) traffic flow model, which is subject to both relaxation time uncertainty in the domain and boundary input disturbance. The boundary input disturbance comes from merging vehicles' velocities at the downstream on-ramp, and we scale the disturbance by a low-pass filter based on the ordinary differential equation (ODE). Then, the ARZ model with the domain uncertainty and boundary input disturbance can be linearized to a coupled ODE-PDE system. Based on the swapping transformation, an adaptive boundary observer with least-squares type parameter estimation is designed to estimate the traffic states, the domain uncertainty, and the boundary input disturbance, simultaneously. The exponential convergence conditions w.r.t. the observer feedback gains are given by employing the Lyapunov technique. Finally, the simulation results are presented to illustrate the effectiveness of the designed adaptive boundary observer.
|
|
ThB21 |
Room 422 |
Human Machine Symbiosis: Perspectives on Emerging Digital Trends and Their
Social Impact I |
Open Invited Session |
Chair: Organ, John | South East Technological University, Ireland |
Co-Chair: Doyle-Kent, Mary | South East Technological University |
Organizer: Organ, John | South East Technological University, Ireland |
Organizer: Doyle-Kent, Mary | South East Technological University |
Organizer: Stapleton, Larry | Waterford Institute of Technology |
Organizer: Kopacek, Peter | TU Wien |
|
13:30-13:50, Paper ThB21.1 | |
Mentorship in Engineering: Women, Inclusivity and Diversity – a Challenge for Our Times (I) |
|
Walsh Shanahan, Breda | South East Technological University |
Doyle-Kent, Mary | South East Technological University |
Keywords: Equality, diversity, and inclusion, Universal access to technology and the digital divide, Young engineers in control
Abstract: More than ever before the fate of humanity and the survival of human kind is an existential crisis. Diverse highly talented teams of professionals are needed to work together in order to survive and thrive into the future. There is a recognised crisis in attracting and retaining women and other minority groups into science, technology, engineering, and mathematics (STEM) professions. This paper looks at the statistical representation of women and minorities in STEM professions such as engineering and information technology (IT). Mentorship programmes have been recognised as beneficial and this research outlines the significance played by mentoring and role models in promoting STEM. It analyses how the current initiatives are performing in their efforts to transform and increase participation in STEM.
|
|
13:50-14:10, Paper ThB21.2 | |
21st Century Engineering Workplace: How an Inclusive Culture Can Deliver Innovation and Value (I) |
|
Hersh, Marion A. | University of Glasgow |
Doyle-Kent, Mary | South East Technological University |
Keywords: Equality, diversity, and inclusion, Universal access to technology and the digital divide, Knowledge society
Abstract: Women and minority groups are still only minimally represented in most engineering workplaces. This is a loss-loss situation which disadvantages these workplaces, engineering as a whole, and the wider society by not taking advantage of all the available talent and reducing the potential for innovation. It also disadvantages women and minority groups who are largely excluded from an interesting profession. Changing this and bringing the engineering profession into the 21st century and beyond will require changes in the culture of the workplace to ensure all members of society are comfortable and can bring their true self to work. This paper looks at how equality, diversity and inclusion in the engineering workplace are understood and what it means to be truly inclusive. It asks can narratives in ethics and engineering EDI inform future practices. It illustrated how an inclusive culture can enable innovation engineering solutions and as a result, tangible value to engineering companies.
|
|
14:10-14:30, Paper ThB21.3 | |
Artificial Intelligence and the World Wide Web: Brain and Friend? (I) |
|
O'Neill, Brenda | South East Technological University, Waterford |
Doyle-Kent, Mary | South East Technological University |
Walsh Shanahan, Breda | South East Technological University |
Byrne, Darren | South East Technological University |
Carew, Peter J. | South East Technological University |
Stapleton, Larry | Waterford Institute of Technology |
Pearson, Sue | Sue Pearson |
Keywords: Knowledge society, Engineering ethics, Human values and value systems
Abstract: This paper looks at artificial intelligence (AI) and society and posits the idea of AI on the World Wide Web as a brain comparing it to the human brain. It frames the WWW as ‘friend’ to all and follows this disturbing train of thought. It speaks to tacit knowledge and tools and compares the work, skill knowledge of the librarians/curators to that of the artisan crafts person. It positions the work of the INSYTE-Cooley Research lab at the heart of this situation. Furthermore, it speaks of an ‘altered reality’ where a dangerous disconnection is occurring, where people are becoming observers of reality because of the abstraction that the screen provides. This spectator view is desensitizing people to what is happening in front of them and will be further fueled by the creation of the ‘metaverse’ in the future. It speaks of the danger of AI going from judgement to calculation without employing human reason and of the danger of humans becoming a passive audience. In this techno centric world it speaks of the amplified importance of tacit knowledge and the development of Human Centered Systems (HCS). It echoes Michael Cooleys thoughts on technology and the place of humanity within a techno-centric world. It speaks of the ethical and moral obligations to society and the danger of disregarding them.
|
|
14:30-14:50, Paper ThB21.4 | |
MementoArtem: A Digital Cultural Heritage Approach to Archiving Street Art (I) |
|
McInerney, Patrick | INSYTE, South East Technological University |
O'Neill, Brenda | South East Technological University, Waterford |
Ffrench, Paul | Memento Artem |
Keywords: Digital culture and cultural heritage, Human values and value systems, Knowledge society
Abstract: Street art can possess a dramatic visual and power. However, they are also potentially subject to weather damage and harm by other means such as defacement, vandalism and even demolition. Commissioning bodies and even artists themselves often regard their work as temporary creations. In a word, they are fragile. The MementoArtem project was established in 2021 and is an exploration of a variety of technologies and appropriate standards to document and archive, not only the physical work of street artists, but also the tacit knowledge of a variety of sources that goes into their production. In this way, street art, like other cultural heritage artefacts, may be digitally preserved for future generations. It is with this in mind that we propose a metaframework for the documentation, storing and dissemination of a semantically-enabled archive of street art.
|
|
14:50-15:10, Paper ThB21.5 | |
Can Action Research Methods Help. Address the Digital Social Sustainability Gap?: An Evaluation and Refinement of the ENRICHER Method Using PAR (I) |
|
O'Neill, Brenda | South East Technological University, Waterford |
Stapleton, Larry | Waterford Institute of Technology |
Carew, Peter J. | South East Technological University |
Keywords: Digital culture and cultural heritage, Human values and value systems, Engineering ethics
Abstract: The digital social sustainability gap narrative (O’Neill & Stapleton, 2022) endeavours to address the digital social sustainability gap by using digital technology for social benefit i.e. opening up dark archives in the digital cultural heritage area. It raises issues of the interoperability between institutions for knowledge sharing, thereby breaking of the disciplinary silos and also breaking the data silos within institutions. It argues for multidisciplinary collaborations, the valorisation of tacit knowledge of co-researchers so that technology does not replace the work of the human but forms a beneficial human machine symbiosis. Further it provides an insight into the ethos-centric perspective of the ENRICHER method developed by the INSYTE-Cooley Research Lab (I-CRL). This study uses an experimental technique within the Participation Action Research (PAR) methodology to valorise human tacit knowledge and intellectual capacity so that they are placed at the heart of the development process. Action research with a combination of the Human Centered Systems (HCS) approach to systems development are combined so that a multidisciplinary group with diverse world views can collaborate to create a new human centered framework for the digitisation of cultural heritage.
|
|
15:10-15:30, Paper ThB21.6 | |
Are Online Social Spaces Further Marginalising Minority Groups in Society? a Case Study of the Experiences of the LGBTQ Community in Ireland (I) |
|
Donnelly, Noeleen | South East Technological University |
Stapleton, Larry | Waterford Institute of Technology |
Keywords: Social and environmental sustainability, Engineering ethics, Equality, diversity, and inclusion
Abstract: Building on earlier research in engineering ethics, this study explores the extent to which automation in digital public spaces, contribute to the marginalization of certain citizen subgroups. This paper focuses on the experiences of the LGBTQ community in both offline and online LGBTQ spaces. We present empirical data gathered from the Irish LGBTQ community. We contend that this country case study, is instructive to the experiences of digital marginalization forces, in other countries and contexts. Ireland is seen as a world leader in LGBTQ rights since the legalization of same-sex marriage by public vote in 2015. In spite of these new freedoms, enshrined also in EU civil liberties, we present evidence that the LGBTQ online space lacks, a safe space for a diversity of genders and sexualities. We conclude that digital public spaces continue to marginalize these communities and we make recommendations for IFAC research and digital public policy.
|
|
ThB22 |
Room 423 |
Control, Mechatronics, and Imaging for Medical Devices and Systems in
Medicine IV |
Open Invited Session |
Chair: Benyo, Balazs | Budapest University of Technology and Economics |
Co-Chair: Moeller, Knut | Furtwangen University |
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 |
|
13:30-13:50, Paper ThB22.1 | |
Novel Assistive Devices for Umbilical Artery Catheterisation (I) |
|
Dixon, Josephine | University of Canterbury |
Chase, J. Geoffrey | University of Canterbury |
Budgett, Rachel | Mechanical Engineering, University of Canterbury |
Caljé-van der Klei, Trudy | Mechanical Engineering, University of Canterbury |
Pooke, Francis Craig | University of Canterbury |
Wallenstien, Matthew | Christchurch Women’s Hospital |
Keywords: Control of physiological and clinical variables, Control of voluntary movements, respiration
Abstract: Abstract: Background: 300+ neonates/year in a New Zealand neonatal intensive care unit (NICU) need umbilical arterial catheterisation (UAC), of whom 7.5% die or have permanent impairment because an umbilical arterial catheter could not be inserted. Complexities associated with the procedure can lead to lengthy procedure times and increased risk of catheterisation failure, increasing the risk of poor outcomes. While several manual techniques are used, very few use assistive devices. Objective: Design and test assistive devices to significantly simplify UAC. Methods: Main requirements include: 1) insertion time <15 minutes; 2) only one practitioner required. The procedure requires two primary tasks: 1) traction (tensioning) of the umbilical cord; 2) dilation of the umbilical artery to admit the (wider, 5F) catheter. A full design analysis addresses these tasks and requirements. Prototypes are evaluated by a NICU clinician using a silicone phantom umbilical cord. Results: A two-device solution was developed, comprising a hands-free traction device and a dilation device. The traction device utilises a small hair-clip like device with torsional spring and stabilising skirt. The dilator comprises an insertor and a sheath. The insertor tip diameter of 0.1 mm allows easy insertion, while the following sheath dilates the artery to allow catheter insertion. All devices are removed after insertion. UAC time decreased an average of 51.8% over 6 tests versus without assistive devices, and only one practitioner was required. Conclusions: The coordination, complexity, and time for UAC were significantly reduced, using simple, novel assistive devices, which could improve outcomes for infants suffering negative outcomes due to UAC insertion failure.
|
|
13:50-14:10, Paper ThB22.2 | |
Frequency Decomposition of Actuated Breast Tissue to Provide Diagnostic Insight (I) |
|
Fitzjohn, Jessica Louise | University of Canterbury |
Zhou, Cong | University of Canterbury |
Chase, J. Geoffrey | University of Canterbury |
Keywords: Healthcare management, disease control, critical care, Clinical validation, Medical imaging and processing
Abstract: Digital Image Elasto Tomography (DIET) is an automated, non-invasive breast cancer screening technology with improving diagnostic potential. DIET screening involves a women lying prone with low-amplitude steady state sinusoidal vibrations applied to the free hanging breast, while surrounding cameras capture the breast surface motion. This paper presents a computationally simple diagnostic algorithm using frequency analysis of this breast surface motion data from a clinical trial using the DIET system involving N=14 women (28 breasts, 13 cancerous). Each breast was segmented into four radial and four vertical segments (16 total) and frequency decomposition of each reference point in each segment was averaged. Frequency content was hypothesised to be similar in healthy breasts among segments in the same vertical band, while stiffer cancerous tissue was hypothesised to effect frequency response, resulting in distinguishable differences and diagnostic insight. An optimal percentage tolerance, used to assess the degree of similarity between the segments, yielded 85% sensitivity and 77% specificity, showing comparable or better diagnostic accuracy than mammography. In addition, receiver operator characteristic (ROC) curve area (AUC) was 0.81, considered excellent. Diagnostic results are promising, added with the benefits of DIET screening, including portability, non-invasive screening, and no breast compression, with potential to increase screening participation and equity, improving outcomes for women.
|
|
14:10-14:30, Paper ThB22.3 | |
Design and Validation of a Low-Cost, Low-Power, Clockwork Insulin Pump (I) |
|
Pooke, Francis Craig | University of Canterbury |
Payne, Matthew | University of Canterbury |
Holder-Pearson, Lui | University of Canterbury |
Chase, J. Geoffrey | University of Canterbury |
Keywords: Intensive and chronic care or treatment, Chronic care and/or diabetes, Artificial pancreas or organs
Abstract: A novel, low-cost (NZ500), and low-power (12 month estimated battery life) insulin pump prototype is presented. The device aims to increase insulin pump uptake by offering a 9-17 times reduction in pump cost, by limiting the inconvenience and economic constraints of pump treatment. Low-cost is achieved by offloading computation from the pump to a smart device via Bluetooth. An innovative pumping mechanism enables long battery life, with all power required to deliver insulin provided by a spring. A clockwork escapement mechanism is integrated with a low-power actuator to provide dosage control. The accuracy of the novel design was assessed using in-vitro testing to IEC Standard 60601-2-24 (2012) and was benchmarked against two commercial insulin pumps. The clockwork pump achieves similar accuracy to the commercial devices for boluses of 0.005 ml, 0.01 ml, and 0.05 ml, with mean errors < 5%. Consistent over-delivery reduces the accuracy of the clockwork pump at the minimum bolus volume of 0.001 ml (8.1% mean error). For all basal rates tested (0.001 mlh -1, 0.005 mlh -1, and 0.01 mlh -1), the clockwork pump demonstrates similar accuracy and improved consistency compared to commercial devices. Redesigning with higher precision hardware will improve pump accuracy, enabling comparable performance to commercial pumps across all boluses and basal rates. The standards-based testing validates the novel pump concept and justifies further development.
|
|
14:30-14:50, Paper ThB22.4 | |
Insulin Pump Accuracy at Low and Minimum Delivery Rates, in Relation to Paediatric Diabetes Care (I) |
|
Payne, Matthew | University of Canterbury |
Pooke, Francis Craig | University of Canterbury |
Holder-Pearson, Lui | University of Canterbury |
Chase, J. Geoffrey | University of Canterbury |
Keywords: Artificial pancreas or organs, Pharmacokinetics and drug delivery, Intensive and chronic care or treatment
Abstract: Incidence of Type 1 Diabetes is increasing rapidly in children. The uptake of insulin pump therapy as a treatment method amongst the paediatric population is also increasing quickly, outstripping the rate of uptake in other groups. Studies have shown varied results regarding the safety of insulin pump therapy in children and adolescents. An investigation was conducted to determine if delivery accuracy of insulin pumps can potentially affect glycaemic outcomes in younger users. Three insulin pumps were tested: A low-cost prototype pump design, and two commercially available insulin pumps at basal rates of 0.025 U/h, 0.1 U/h and 1 U/h. Bolus accuracy was also tested at a range of bolus sizes between 0.025 U and 1 U. Testing was completed in accordance with IEC60601-2-24, with some modifications made to improve accuracy and ensure results are more generalisable to real world insulin pump use. Results showed large inaccuracies at smaller dose sizes and potential for insulin pump accuracy errors to cause a clinically relevant shift in blood glucose values, especially at the smaller dose sizes and basal rates used by children and those sensitive to insulin. Further testing is needed with a wider range of commercial insulin pumps to determine if these errors are present in all devices.
|
|
14:50-15:10, Paper ThB22.5 | |
Modeling the Correlation of Human Vertebral Body Volumes (I) |
|
Szabó, Bálint | Budapest University of Technology and Economics |
Szlávecz, Ákos | Budapest University of Technology and Economics |
Bazso, Sandor | Budapest University of Technology and Economics |
Somogyi, Péter | Budapest University of Technology and Economics |
Kovács, Katalin | Széchenyi István University |
Viola, Arpad | Department of Neurotraumatology, Semmelweis University, Budapest |
Benyo, Balazs | Budapest University of Technology and Economics |
Keywords: Medical imaging and processing, Quantification of physiological parameters for diagnosis and treatment assessment, Biomedical system modeling, simulation and visualization
Abstract: Anatomical parameters of the human body strongly correlate with each other. Modelling these dependencies enables the creation of a realistic anatomical human body model that can be parameterized. Such a model can be used for several diagnostic processes to identify abnormalities or even give guidance in surgical interventions. This paper proposes a probabilistic model describing the dependencies between the vertebral body volumes of humans from the Caucasian human race. As demonstrated, the proposed model can accurately describe the relationship between the vertebral body volumes and is used for the prediction of an unknown vertebral volume based on a known one. The probabilistic model is created by using the CT segmentation of 37 patients.
|
|
ThB23 |
Room 501+502 |
Reinforcement Learning and Deep Learning in Control I |
Regular Session |
Chair: Paschalidis, Ioannis | Boston University |
Co-Chair: Cerf, Sophie | INRIA |
|
13:30-14:10, Paper ThB23.1 | |
Combining Neural Networks and Control: Potentialities, Patterns and Perspectives |
|
Cerf, Sophie | INRIA |
Rutten, Eric | INRIA Rhône Alpes |
Keywords: Machine learning in modelling, prediction, control and automation, Data fusion and data mining in control, Reinforcement learning and deep learning in control
Abstract: Machine learning tools are widely used for knowledge extraction, modeling, and decision tasks ; a range of problems that Control Theory also tackles. Their relations have been largely explored by looking at stochastic control and Markov Decision Processes, due to the proximity of their formulations. However, novel links between machine learning and deterministic control are emerging; combining both approaches, e.g. by performing identification with learning, or controlling the training process. The recent flourishing literature is vast: there is a need to identify challenges, trends and opportunities on this interface. This survey contributes i) to the compared analysis of both fields. ii) Based on literature review, a categorization of combinations of learning and control is drawn. In the control framework, learning has been used for modeling, controllers tuning or adaptation, generating a controller or as a controller itself, for translating complex objectives, or checking controlled systems. Conversely, in the learning framework, control is used for tuning hyperparameters, selecting or generating training data, as the training or decision-making algorithm itself or to guarantee learning properties. iii) Finally, discussions on the literature open novel promising combinations to be explored, such as control of neural networks’ training process.
|
|
14:10-14:30, Paper ThB23.2 | |
Reinforcement Learning in an Adaptable Chess Environment for Detecting Human-Understandable Concepts |
|
Hammersborg, Patrik | Norwegian University of Science and Technology |
Strümke, Inga | Norwegian University of Science and Technology |
Keywords: Reinforcement learning and deep learning in control, Machine learning, Knowledge-based control
Abstract: Self-trained autonomous agents developed using machine learning are showing great promise in a variety of control settings, perhaps most remarkably in applications involving autonomous vehicles. The main challenge associated with self-learned agents in the form of deep neural networks, is their black-box nature: it is impossible for humans to interpret deep neural networks. Therefore, humans cannot directly interpret the actions of deep neural network based agents, or foresee their robustness in different scenarios. In this work, we demonstrate a method for probing which concepts self-learning agents internalise in the course of their training. For demonstration, we use a chess playing agent in a fast and light environment developed specifically to be suitable for research groups without access to enormous computational resources or machine learning models.
|
|
14:30-14:50, Paper ThB23.3 | |
Opportunities and Challenges from Using Animal Videos in Reinforcement Learning for Navigation |
|
Giammarino, Vittorio | Boston University |
Queeney, James | Boston University |
Carstensen, Lucas | Boston University |
Hasselmo, Michael | Boston University |
Paschalidis, Ioannis | Boston University |
Keywords: Reinforcement learning and deep learning in control, Machine learning in modelling, prediction, control and automation
Abstract: We investigate the use of animal videos (observations) to improve Reinforcement Learning (RL) efficiency and performance in navigation tasks with sparse rewards. Motivated by theoretical considerations, we make use of weighted policy optimization for off-policy RL and describe the main challenges when learning from animal videos. We propose solutions and test our ideas on a 2D navigation task. We show how the use of animal videos improves performance over RL algorithms that do not leverage such observations.
|
|
14:50-15:10, Paper ThB23.4 | |
Autoencoder Neural Networks for LPV Embedding of Nonlinear Systems |
|
Sadeghzadeh, Arash | ENAC |
Garoche, Pierre-Loic | ENAC Toulouse |
Keywords: Reinforcement learning and deep learning in control, Linear parameter-varying systems, Machine learning in modelling, prediction, control and automation
Abstract: In this paper, the problem of automated generation of linear parameter-varying (LPV) state-space models is addressed. A deep neural network (DNN) is developed to embed the dynamical behavior of a nonlinear (NL) system into an LPV model with predefined number of scheduling variables which are the NL functions of the states. Leveraging the Autoencoder (AE) neural networks (NN) and using the input-output plant data, a scheduling NL mapping is defined. The developed LPV model depends affinely on the scheduling variables. Since the proposed method to derive LPV model is based on input-output plant data, the explicit NL equations of the plant are not required. The upper and lower bounds on the scheduling variables can be computed by solving convex optimization problems. The effectiveness of the proposed method is evaluated on a benchmark example.
|
|
15:10-15:30, Paper ThB23.5 | |
Safe Reinforcement Learning for Autonomous Navigation of a Driveable Vertical Mast Lift |
|
Brescia, Walter | Politecnico Di Bari |
Maci, Antonio | Politecnico Di Bari |
De Cicco, Luca | Politecnico Di Bari |
Mascolo, Saverio | Politecnico Di Bari |
Keywords: Reinforcement learning and deep learning in control, Machine learning in modelling, prediction, control and automation, Industry 4.0
Abstract: In this work, we consider the issue of controlling a Driveable Vertical Mast Lift (DVML) to autonomously navigate an environment while ensuring required safety constraints. DMVL are industrial vehicles used in several applications, f.i. in logistics and smart agriculture, to allow operators placed in a basket accessing elevated worksites. When driving such machines, operators are exposed to hazards that could lead to potentially serious accidents. Reinforcement Learning (RL) is a data-driven approach that is increasingly being used to control complex systems. This work investigates the advancements in the field of Safe RL from a practical perspective, employing several state-of-art algorithms to equip a DVML with autonomous driving capabilities. We highlight how benchmark environments, while satisfactorily affirming Safe RL methodologies as proof-of-concepts, can widen the gap that prevents such methodologies from both being applied in real scenarios and becoming much more popular in industrial use-cases.
|
|
ThB24 |
Room 503 |
Sustainable Transportation and Energy Systems: Automation and Optimization
I |
Open Invited Session |
Chair: Parodi, Luca | University of Genoa |
Co-Chair: Ferro, Giulio | Università Degli Studi Di Genova |
Organizer: Parodi, Luca | University of Genoa |
Organizer: Ferro, Giulio | Università Degli Studi Di Genova |
Organizer: Paolucci, Massimo | University Di Genova |
Organizer: Robba, Michela | University of Genoa |
Organizer: Dotoli, Mariagrazia | Politecnico Di Bari |
Organizer: Majanne, Yrjö | Tampere University |
Organizer: Ennassiri, Yassine | University of Genoa |
|
13:30-13:50, Paper ThB24.1 | |
Stochastic Traffic Assignment with Electric Vehicles: A Convex Optimization Approach (I) |
|
Aicardi, Michele | Univ. of Genova |
Ferro, Giulio | Università Degli Studi Di Genova |
Minciardi, Riccardo | Univ of Genova |
Robba, Michela | University of Genova |
Keywords: Control of large-scale systems, Smart grids, Advanced control technology
Abstract: Electric vehicles and charging stations are increasing all over the world to reduce emissions at the city level. In order to analyze traffic flows and quantify the demand for energy recharge, it is necessary to model users’ choices taking into account different kinds of traffic flows. In this paper, attention is focused on the formalization of the joint traffic and energy demand assignment conditions over a traffic network in presence of electric vehicles (EVs). Specifically, the so-called stochastic user equilibrium (SUE) conditions are used to define the steady state behaviour of a generic traffic network in which some arcs are equipped with EV charging stations. A convex optimization problem is defined and solved, which is equivalent to the solution of the nonlinear and nonconvex set of SUE conditions under a multinomial Logit user’s choice function. A real case study, related to a touristic area in the Liguria Region (from Genova airport to Portofino), is considered.
|
|
13:50-14:10, Paper ThB24.2 | |
Electric Vehicle Charge Planning by Deep Reinforcement Learning (I) |
|
Roccotelli, Michele | Polytechnic of Bari |
Fanti, Maria Pia | Polytechnic of Bari |
Mangini, Agostino Marcello | Politecnico Di Bari |
Keywords: Neural networks in process control, Intelligent decision support systems, Smart grids
Abstract: In this paper, we study the problem of planning the charging of an electric vehicle (EV) for long distance trips. In particular, a dedicated tool is needed in order to suggest the driver the best traveling and charging plan based on her/his preferences and on the available charge infrastructures along the route. An ad-hoc tool is developed using Matlab and Simulink software in order to model the EV energy charging/discharging, and to optimize the trip plan based on three alternative goals: minimizing the travel time; minimizing the charging cost; optimizing travel time and cost. The proposed model is based on the use of Deep Reinforcement Learning (DRL) algorithm in which an agent is rewarded or penalized while learning the best charging options along the route according to the three above goals. In particular, in a dynamic energy market context, the model is designed to be robust at energy price variations and at cruise speed variations as well. In addition, a dashboard is designed and developed to provide an user-friendly interface to set the EV and trip parameters and to monitor the trip planning results. A case study demonstrates the effectiveness of the proposed tool.
|
|
14:10-14:30, Paper ThB24.3 | |
Laser-Based Dynamic Optical Wireless Power Transfer for Electrified Vehicles Covered with Solar Cells (I) |
|
Nguyen, Hoa | Kyushu University |
Keywords: Smart grids, Control of renewable energy resources, Modeling and simulation of power systems
Abstract: This research proposes and theoretically analyzes a dynamic optical wireless power transfer (OWPT) system for wireless charging of aerial and ground electric vehicles (EVs). In the proposed system, an overhead facility is utilized to host laser transmitters, while solar arrays are attached on EVs to be energy receivers. Moreover, laser transmitters are able to rotate, point upward and downward to wirelessly charge aerial and ground EVs. Owing to the movement of EVs, the wirelessly transmitted power and energy to EVs are varying with time and distance, hence are not as simple as in the case of static wireless charging, i.e. when EVs are stopped or hovering. This paper therefore proposes an analytical analysis for the dependence of wirelessly transmitted laser power and energy to moving EVs on the transmitting distance, utilizing the exponential integral function. The derived results reveal that there exist a unique maximum power point and a unique maximum energy point, due to the monotonic increase and decrease of the transmitted power and energy. These give rise to determining the optimal distances at which the wirelessly transmitted laser power and energy are maximum. Numerical simulations are then carried out to validate and illustrate theoretical results.
|
|
14:30-14:50, Paper ThB24.4 | |
Automatic Transmission Grid Control of Active Distribution Networks (I) |
|
Hinners, Holm | University of Bremen |
Contreras, Sergio | Universität Bremen |
Myrzik, Johanna | University Bremen |
Keywords: Modeling and simulation of power systems, Control of renewable energy resources, Real time simulation and dispatching
Abstract: Active distribution networks (ADNs) intend to manage the escalating computational complexity of renewable power grids by providing controlled subdivisions which support the operation of the transmission grid in some way. They display complex dynamical behavior greatly influenced by the chosen controllers and themselves pose a variety of challenges for the transmission grid. This work describes all elements of a continuous-time controller architecture for ADNs connected to each other through the transmission grid in a low-carbon environment including the controllers of the ADNs and the controllers of the transmission grid. Time-domain simulations are carried out for validation to illustrate the response, with a more traditional integral controller used for comparison.
|
|
14:50-15:10, Paper ThB24.5 | |
User-On-Demand Renewable Energy Supply System Using Modified DC-Bus Signaling (I) |
|
Tsuno, Katsuhiko | RIKEN RAP |
Koike, Kayo | RIKEN RAP |
Fujii, Katsushi | RIKEN |
Ogawa, Takayo | RIKEN |
Wada, Satoshi | RIKEN RAP |
Keywords: Control of renewable energy resources, Control of distributed systems
Abstract: Electric power converted from renewable energy is a common way to use. However, the user-on-demand supply of electric power cannot be guaranteed because renewable energy sources fluctuate depending on the natural conditions. To solve this problem, an energy system is required to control the power supply in response to the power demand. For this purpose, not only a relatively large amount of energy is stored, but also a rapid response to power fluctuation is necessary. The control method is usually complicated because the system requires multiple storage devices to satisfy the purpose. We proposed a relatively simple method to control the energy system. In this study, the control method, that is, the modified DC-bus signaling energy supply system with hydrogen storage, is discussed.
|
|
15:10-15:30, Paper ThB24.6 | |
On the Equivalence of Battery Storage and Demand Response: Theoretical Analysis and Convex Optimization (I) |
|
Mudumbai, Raghuraman | University of Iowa |
Krishnamurthy, Muthu | University of Iowa |
Dasgupta, Soura | University of Iowa |
Keywords: Optimal operation and control of power systems, Control of renewable energy resources, Smart grids
Abstract: Energy storage and demand response are two technologies that are both capable of smoothing over load fluctuations and variations in intermittent wind and solar generation in the electric grid. In this sense, demand response can be thought of as a type of energy storage; indeed, demand response technologies are often referred to as “virtual storage” devices. However, this implied equivalence between demand response and energy storage has never been subjected to a rigorous mathematical analysis. In this paper, we derive the amount of virtual storage capacity provided by a given amount of load flexibility for a idealized electric grid where the load and a portion of the generation are independent memoryless random processes. We find that the virtual storage capacity of demand response decreases with the amount of demand flexibility already existing on the grid. We formulate an optimization problem to find the best combination of storage and demand response that balances the intermittent generation with the load at minimum cost. We hypothesize that this optimization problem is convex and derive some properties of the optimal solution under this hypothesis.
|
|
ThBT1 |
Hall A-1 |
Robust Control Systems |
Interactive Session |
Chair: Sznaier, Mario | Northeastern University |
Co-Chair: Xin, Xin | Okayama Prefectural University |
|
13:30-15:30, Paper ThBT1.1 | |
Dissipativity-Based Robust Control with H-Infinity Optimal Performance |
|
LoCicero, Ethan Jeffrey | Duke University |
Bridgeman, Leila | Duke University |
Keywords: Passivity-based control, Robust controller synthesis, Robust linear matrix inequalities
Abstract: A controller is designed to minimize the closed-loop H-infinity norm and satisfy an open-loop dissipativity constraint. The H-infinity norm optimizes performance of a nominal LTI plant approximation, while the dissipativity constraint ensures stability of the true plant, which is composed of nonlinear and uncertain subsystems robustly characterized by input-output properties. A local minimum to the NP-hard problem is found using the convex concave procedure, and an initialization is proposed that guarantees feasibility for a wide array of special cases. A numerical experiment compares the proposed design to the H-infinity optimal controller for a network of nonlinear and LTI systems.
|
|
13:30-15:30, Paper ThBT1.2 | |
Computation of the Phase and Gain Margins of MIMO Control Systems |
|
Srazhidinov, Radik | Hong Kong University of Science and Technology |
Zhang, Ding | Hong Kong University of Science and Technology |
Qiu, Li | Hong Kong Univ. of Sci. & Tech |
Keywords: Robust control (linear case), Linear multivariable systems, Time-invariant systems
Abstract: This paper solves the problem of exact computation of the phase and gain margins of multivariable control systems. These stability margins are studied using the concept of the Davis-Wielandt shell of complex matrices. Calculation of the phase and gain margins requires solving a quadratically constrained quadratic program (QCQP) and a parametrized quadratically constrained problem, respectively, which are known to be difficult in general. The semidefinite relaxation (SDR) technique is often used as a computationally efficient approximation technique to solve QCQPs. It turns out that the QCQPs formulated from the phase and gain margin problems in this paper fall under the class of quadratic optimization problem, for which the SDR is exact. This is so in the sense that optimal values of the QCQP and its SDR are equal, and an optimal solution for the original QCQP problem can be obtained from an optimal solution of its SDR. Thus, we are able to propose computationally efficient algorithms to compute the phase and gain margins with an arbitrarily high precision. Numerical examples are given to illustrate the effectiveness of the proposed algorithms.
|
|
13:30-15:30, Paper ThBT1.3 | |
Mixed mathcal{H}_2/mathcal{H}_infty-Policy Learning Synthesis |
|
Molu, Lekan | Microsoft Corporation |
Keywords: Robust control, Data-driven optimal control, Machine learning in modelling, prediction, control and automation
Abstract: A robustly stabilizing optimal control policy in a model-free mixed mathcal{H}_2/mathcal{H}_infty-control setting is here put forward for counterbalancing the slow convergence and non-robustness of traditional high-variance policy optimization (and by extension policy gradient) algorithms. Leveraging It^{o}'s stochastic differential calculus, we iteratively solve the system's continuous-time (closed-loop) generalized algebraic Riccati equation(GARE) whilst updating its admissible controllers in a two-player, zero-sum differential game setting. Our new results are illustrated by learning-enabled control systems which gather previously disseminated results in this field in one holistic data-driven presentation with greater simplification, improvement, and clarity.
|
|
13:30-15:30, Paper ThBT1.4 | |
Structured H-Infinity Design for the LISA Mission Accelerometer Mode |
|
Navarro-Tapia, Diego | Technology for Aerospace Control (TASC) Ltd |
Marcos, Andres | Universidad Carlos III De Madrid |
Keywords: Robust control, Space exploration and transportation, Controller constraints and structure
Abstract: This article presents the application of the structured H-infinity control approach to the design of the LISA mission accelerometer mode. This joint ESA/NASA mission will be the first space-based gravitational wave observatory and is characterized by very stringent scientific constraints resulting in unprecedented control challenges in terms of precision, accuracy, and complexity. The results presented in here were the first demonstration step performed within an ESA study tasked with surveying, trading-off, and applying advanced control techniques to LISA. In addition to showing the methodological gains and design capabilities of the structured H-infinity approach, the effects of hardware changes as well as control switching were also analyzed for the designed controllers providing good insight on the way forward to reduce the associated transients. The results presented in this article laid the groundwork, and design process, to subsequently design and validate the full LISA accelerometer mode.
|
|
13:30-15:30, Paper ThBT1.5 | |
Power System Stabilization under Prespecified State-Space Bounds |
|
Vrazhevsky, Sergey | ITMO University |
Furtat, Igor | Institute of Problems of Mechanical Engineering Russian Academy |
Gushchin, Pavel | Gubkin Russian State University of Oil and Gas (National Researc |
Keywords: Robust control, Power systems, Output feedback control
Abstract: The article deals with a power system post-fault stabilization problem using a new control technique that ensures system output existence strictly under prespecified state-space bounds. A linearized model of the power generator under unknown bounded disturbances is considered. A new non-linear control technique based on specific coordinate transformation is proposed. Closed-loop system stability is rigorously proven and verified via computer simulation.
|
|
13:30-15:30, Paper ThBT1.6 | |
Real-Time Control and Power Management Strategies of PV/Battery Standalone System |
|
Benzaouia, Mohammed | National School of Applied Sciences, Mohamed First University, O |
Rabhi, Abdelhamid | M.I.S (Modelisation, Information Et Systèmes) |
Hajji, Bekkay | National School of Applied Sciences, Mohamed First University, O |
Benzaouia, Soufyane | LIS UMR CNRS 7020, of Aix Marseille University |
Midavaine, Herve | Laboratory of Modelisation, Information and Systems – MIS |
Oubbati, Brahim Khalil | University of Laghouat |
Keywords: Power systems, Real time optimization and control, Control of renewable energy resources
Abstract: In this paper, novel control and power management strategies based on the fuzzy logic of an autonomous PV/battery system suitable to water pumping applications is proposed and experimentally validated. The PV panel provides the steady-state energy demand according to the climatic conditions and the battery ensures the energy balance at the load level (PMDC motor unit). The system includes two converters, a unidirectional DC-DC converter, and a bidirectional DC-DC converter, which are used as intermediaries between the DC bus, the PV, and the battery respectively. The maximum power extraction (MPP) is ensured via a feed-forward neural network-based MPPT, generating the appropriate duty cycle for the primary converter. The power management system and the control strategy allow the generation of reference currents within the limits of the battery's state of charge. Experimental studies on a prototype system have been performed to verify the effectiveness of the proposed approaches.
|
|
13:30-15:30, Paper ThBT1.7 | |
A Generalisation of the Secant Criterion |
|
Pates, Richard | Lund University |
Keywords: Robust control (linear case), Uncertain systems, Linear systems
Abstract: The cyclic feedback interconnection of n subsystems is the basic building block of control theory. Many robust stability tools have been developed for this interconnection. Two notable examples are the small gain theorem and the Secant Criterion. Both of these conditions guarantee stability if an inequality involving the geometric mean of a set of subsystem indices is satisfied. The indices in each case are designed to capture different core properties; gain in the case of the small gain theorem, and the degree of output-strict-passivity in the Secant Criterion. In this paper we identify entire families of other suitable indices based on mappings of the unit disk. This unifies the small gain theorem and the Secant Criterion, as well as a range of other stability criteria, into a single condition.
|
|
13:30-15:30, Paper ThBT1.8 | |
H-Infinity Control of Scalar Nonlinear Systems |
|
Ashraf, Fawad Farooq | CESAT, Islamabad |
Khan, Hafiz Zeeshan Iqbal | Centers of Excellence in Science and Applied Technologies, Islam |
Haydar, Muhammad Farooq | Institute of Space Technology |
Riaz, Jamshed | Institute of Space Technology, Islamabad |
Keywords: Robust control, Robust controller synthesis, Disturbance rejection
Abstract: The L2 disturbance attenuation control or the nonlinear H-infinity control of a nonlinear system requires solving the Hamilton-Jacobi-Isaacs (HJI) partial differential inequality, which is generally a difficult undertaking. Though there are inverse optimal approaches, they have limited utilization from a practical point of view. In this work, a novel approach of state feedback H-infinity control is proposed for scalar nonlinear systems using piecewise affine bounds of scalar valued nonlinear functions. An LMI based systematic procedure is proposed. To illustrate the proposed method, an example of a scalar nonlinear system possessing significant nonlinearity has been considered. To demonstrate the effectiveness of the proposed scheme, it is compared with Linear Parameter Varying (LPV) based state feedback H∞ control, using quasi-LPV models based on Taylor series expansion.
|
|
13:30-15:30, Paper ThBT1.9 | |
Satellite Dynamics Toolbox Library: A Tool to Model Multi Body Space Systems for Robust Control Synthesis and Analysis |
|
Sanfedino, Francesco | Institut Supérieur De l'Aéronautique Et De L'Espace |
Alazard, Daniel | Université De Toulouse - ISAE |
Kassarian, Ervan | DyCSyt |
Somers, Franca | ONERA, the French Aerospace Lab |
Keywords: Robust control (linear case), Vibration and modal analysis, Probabilistic robustness
Abstract: The level of maturity reached by robust control theory techniques nowadays contributes to a considerable minimization of the development time of an end-to-end control design of a spacecraft system. The advantage offered by this framework is twofold: all system uncertainties can be included from the very beginning of the design process; the validation and verification (V&V) process is improved by fast detection of worst-case configurations that could escape to a classical sample-based Monte Carlo simulation campaign. Before proceeding to the control synthesis and analysis, a proper uncertain plant model has to be available in order to push these techniques to their limits of performance. In this spirit, the Satellite Dynamics Toolbox Library (SDTlib) offers many features to model a spacecraft system in a multi-body fashion on SIMULINK. Parametric models can be easily built in a Linear Fractional Transformation (LFT) form by including uncertainties and varying parameters with minimal number of repetitions. Uncertain Linear Time Invariant (LTI) and uncertain Linear Parameter-Varying (LPV) controllers can then be synthesized and analyzed in a straightforward way. The authors present in this article a tutorial, that can be downloaded at https://nextcloud.isae.fr/index.php/s/XDfRfHntejHTmmp, to show how to deal with an end-to-end robust design of a spacecraft mission and to provide to researchers a benchmark to test their own algorithms.
|
|
13:30-15:30, Paper ThBT1.10 | |
Finite-Time Boundedness of Polytopic Uncertain Systems with Guaranteed Cost Output Feedback Control |
|
Dinesh, Ajul | Indian Institute of Technology Dharwad |
Mulla, Ameer | Indian Institute of Technology Dharwad |
Keywords: Robust control (linear case), Uncertain systems, Robust linear matrix inequalities
Abstract: A problem of designing robust guaranteed cost reduced-order output feedback controllers for finite-time boundedness of linear time-varying uncertain systems is considered in this paper. Assuming the system parameters to lie in a polytopic set, differential linear matrix inequality (DLMI) conditions for the design of reduced-order dynamic controllers to handle worst-case exogenous disturbances are derived. The designed controller guarantees the cost on considered disturbance attenuation performance on the system to be below an upper bound, while simultaneously satisfying the conditions for finite-time boundedness and finite L2 gain. Numerical simulations are carried out to demonstrate the applicability of the proposed method in bounding the system trajectories to a predefined set.
|
|
13:30-15:30, Paper ThBT1.11 | |
Strong Stabilization of the Acrobot at the Down-Up Equilibrium Point |
|
Wang, Ziyu | Southeast University |
Xin, Xin | Okayama Prefectural University |
Liu, Yannian | Southeast University |
Keywords: Robust control (linear case), Output feedback control (linear case), Robots manipulators
Abstract: In this paper, the strong stabilization of the Acrobot at the Down-Up equilibrium point is addressed, with the first link being downward and the second link being upright. By converting the strong stabilization of the Acrobot at the Down--Up equilibrium point equivalently to the existence and design of a stable stabilizing controller for a fourth-order single-input single-output linear plant with adjustable zeros, a pair of poles on the imaginary axis, and a pair of real poles located symmetrically with respect to the origin, this paper has three main contributions. Firstly, the existence of a stable stabilizing controller for any Acrobot which is linearly controllable at the Down--Up equilibrium point is proved by showing the range of the adjustable zero via adjusting a parameter of the output signal. Secondly, a necessary and sufficient condition on the mechanical parameters of the Acrobot is provided to guarantee the existence of a second-order stable stabilizing controller for the Acrobot around its Down--Up equilibrium point. Thirdly, a direct method is presented to design a second-order stable controller, whose transfer function is preset with three parameters. By utilizing the Lienard--Chipart criterion for a fourth-order polynomial, the necessary and sufficient conditions on these parameters for achieving the strong stabilization are obtained, which are expressed in a cascade form for obtaining these parameters conveniently. A numerical example is presented to validate the effectiveness of the proposed method.
|
|
13:30-15:30, Paper ThBT1.12 | |
Admissibility Analysis and Control for Discrete-Time Singular Systems with Interval Time-Varying Delay |
|
Lee, Ching-Min | I-Shou Univ |
Cheng, Chun-An | I-Shou University |
Keywords: Descriptor systems, Robust control (linear case), Time-delay systems
Abstract: This paper mainly investigates an admissibility analysis and controller design problem for an uncertain discrete-time singular system with delayed states. The time-varying delay is within an interval whose lower bound may be greater than zero. Using a modified finite sum inequality and choosing a suitable Lyapunov-Krasovskii function, we derive a set of LMI-based sufficient delay-dependent conditions for the admissibility analysis and controller synthesis problem, respectively. In the end, a numerical example shows the effectiveness and validity of the proposed approach.
|
|
ThBT2 |
Hall A-2 |
Adaptive Control |
Interactive Session |
Chair: Shi, Zongying | Tsinghua University |
Co-Chair: Mizumoto, Ikuro | Kumamoto Univ |
|
13:30-15:30, Paper ThBT2.1 | |
Adaptive Compensation of Unmatched Disturbances in Unstable MIMO LTI Plants with Distinct Input Delays |
|
Nikiforov, Vladimir O. | ITMO University |
Paramonov, Aleksei | ITMO University |
Gerasimov, Dmitry | ITMO University |
Keywords: Adaptive control, Time-delay systems, Linear multivariable systems
Abstract: The paper concerns the problem of adaptive compensation of unmatched disturbances in linear time-invariant (LTI) multi-input multi-output (MIMO) unstable plants with multiple distinct input delays. The external disturbances affect both the input and the output of the plant and are represented by multi-harmonic signals with unknown parameters (frequencies, phases, and amplitudes). The paper extends previous results on adaptive compensation of unmatched disturbances to the case of distinct input delays. To overcome the problem of multiple distinct input delays, a special scheme of the disturbance prediction is proposed and used for design of the adaptive control law.
|
|
13:30-15:30, Paper ThBT2.2 | |
Adaptive Control of LTV Systems with Uncertain Periodic Coefficients |
|
Gerasimov, Dmitry | ITMO University |
Popov, Anton | ITMO University |
Ngo, Dang Hien | ITMO University |
Nikiforov, Vladimir O. | ITMO University |
Keywords: Adaptive control, Time-varying systems, Observers for linear systems
Abstract: The paper considers the control problem for a class of uncertain linear time-varying systems. The time-varying (TV) parameters are represented by multisinusoidal functions with a priori unknown amplitudes, phases, and frequencies of harmonics. The maximum numbers of the harmonics are known. To compensate the influence of the TV parameters on the closed-loop system, based on internal model principle, TV parameters observers are designed, and the plant model is represented in the parameterized form with constant unknown parameters. This form is used for design of adaptive backstepping controller with {em modular identifiers} with improved parameters tuning.
|
|
13:30-15:30, Paper ThBT2.3 | |
Composite Model-Reference Adaptive Control with Least-Squares Parameter Estimator |
|
Costa, Ramon R. | Federal University of Rio De Janeiro |
Keywords: Adaptive control, Lyapunov methods
Abstract: This work presents a new design of a composite model-reference adaptive control (MRAC) with a least-squares parameter estimator. The objective of the design is to preserve the remarkable transient adaptation characteristic obtained by a modified MRAC algorithm recently introduced and, at the same time, enjoy the superior parameter convergence performance of a least-squares estimator. The algorithm employs two different estimators for the same controller parameter, one updated by a gradient law driven by the tracking error and the other updated by a least-squares algorithm driven by a prediction error. In this way, the performance of each one is kept unchanged. The existence of a Lyapunov function assures the global uniform stability of the proposed composite adaptive scheme and simulation results confirm and illustrate its properties.
|
|
13:30-15:30, Paper ThBT2.4 | |
Transient Improvement of Model-Reference Adaptive Control and Parameter Convergence Rate Analysis |
|
Peixoto, Alessandro Jacoud | COPPE/Federal University of Rio De Janeiro (UFRJ) |
Pereira-Dias, Diego | Federal University of Rio De Janeiro |
Costa, Ramon R. | COPPE - Federal Univ of Rio De Janeiro |
Keywords: Adaptive control, Output feedback control (linear case), Tracking
Abstract: The parameter convergence analysis of a modified model-reference adaptive control (M-MRAC) algorithm is presented. The plants considered are continuous with relative degree one. It is verified that the M-MRAC scheme approaches the MRAC scheme when a control design gain increases. Moreover, before this gain reaches high values, the M-MRAC improves the update parameters' convergence. This analysis is performed by noting a clear connection between the M-MRAC and the conventional MRAC by adding a control output injection term. The methodology developed allows for estimating the parameter convergence rate, and simulation results illustrate the improvement in the transient behavior and the parameter convergence attained with the analyzed adaptive schemes.
|
|
13:30-15:30, Paper ThBT2.5 | |
Enhanced Motion Accuracy in Industrial Feed Drive Systems Using Simple Adaptive Control with a Jerk-Based Augmented Signal |
|
Nyobuya, Haryson Johanes | Toyohashi University of Technology |
Halinga, Mathias Sebastian | Toyohashi University of Technology |
Uchiyama, Naoki | Toyohashi University of Technology |
Keywords: Adaptive control, Motion control systems, Mechatronic systems
Abstract: In precision motion technology, motion accuracy is crucial to eliminate potential effects of screw compliance and improve the performance of feed drive systems. This study focuses on motion accuracy improvement for feed drive systems using simple adaptive control (SAC) technique. Almost strictly positive real (ASPR) is a key property to implement SAC to a system. The jerk-based augmented output signal is proposed for the ASPR property that includes velocity, acceleration, and jerk signals. The proposed approach allows the controller to achieve high tracking accuracy and faster adaptation by placing zeros of the controlled system at appropriate locations. To verify the feasibility of the proposed approach, control simulations are conducted and the results are compared with a typical parallel feedforward compensation method. Simulation results revealed that the proposed approach reduces tracking error significantly.
|
|
13:30-15:30, Paper ThBT2.6 | |
Stabilizing Unknown Nonlinear Systems Via Decentralized High-Gain Adaptive Control |
|
Kawano, Yu | Hiroshima University |
Sun, Zhiyong | Eindhoven University of Technology (TU/e) |
Keywords: Adaptive control, Distributed robust controller synthesis, Positive systems
Abstract: In this paper, we study decentralized adaptive stabilization for unknown nonlinear systems with square input matrix-valued functions. This problem formulation arises, e.g., in the context of nonlinear networks, where each scalar subsystem can implement its local controller. We show that if the input matrix-valued function possesses a kind of diagonally dominant properties, decentralized stabilization can be achieved by making each local control gain sufficiently large without knowing the exact system dynamics. Furthermore, when each local gain is updated based on the corresponding local information, the boundedness and convergence of both system dynamics and adaptive local gains are guaranteed.
|
|
13:30-15:30, Paper ThBT2.7 | |
Neural-Adaptive Switching Control of Task-Space Objectives on Strict-Feedback Robot |
|
Doctolero, Samuel | University of Calgary |
Westwick, David | University of Calgary |
Keywords: Adaptive control, Stability of hybrid systems, Switching stability and control
Abstract: Switching between tasks in robot applications is necessary for autonomous behaviour, requiring a control framework for switching between objectives. Thus, this paper proposes a switching control framework that allows transitions in position-dependent objectives for robot systems in strict-feedback form with adaptive capabilities. The proposed controller integrates artificial neural networks in two ways; one approximates control transforms while another approximates additive terms. Furthermore, the proposed method includes a dynamic damped inverse to ensure the invertible control transform matrices. The proposed controller is derived using the backstepping method and is stable in a Lyapunov sense. The proposed task-switching controller is first demonstrated on a generic robot manipulator. Then, a simulated two-degree-of-freedom manipulator with a camera at the end-effector tasked with position tracking and visual servoing verifies the capabilities of the proposed controller. A baseline switching controller shows that the proposed controller has superior performance, specifically, root mean square (RMS) error and control effort. Also, executing the simulation for multiple cycles shows that the proposed controller’s artificial neural network and adaptive laws are stable.
|
|
13:30-15:30, Paper ThBT2.8 | |
A New Adaptive Suboptimal Controller for a Class of Linear Discrete-Time Systems with Unknown Bounded Disturbances |
|
Azarskov, Valerii | National Aviation University |
Solovchuk, Klavdiia | Scientific Research Forensic Center of the MIA of Ukraine |
Volkov, Oleksandr | International Research and Training Center for Information Techn |
Zhiteckii, Leonid | Institute of Cybernetics |
Keywords: Adaptive control, Closed loop identification, Estimation theory
Abstract: This paper deals with adaptive suboptimal control of linear discrete-time, time-invariant, minimum phase, scalar systems in the presence of arbitrary bounded unmeasurable disturbances where upper and lower bounds are a priori unknown. The distinguishing feature of the systems to be controlled is that there is no information concerning a priori knowledge of a bounded set to which the unknown parameters of these systems belong. Novelty of this paper is that, instead of unknown a priori membership set of parameters, the peculiar a posteriori membership sets are designed via the use of the measured signals. The adaptive suboptimal control algorithm utilizing this approach is proposed. The properties of the adaptive controller including the convergence of the adaptation procedure and also the ultimate boundedness of system’s signals are established. To demonstrate an efficiency of this controller and support the theoretical study, simulation results are presented.
|
|
13:30-15:30, Paper ThBT2.9 | |
Fully Distributed Robust Adaptive Formation Control for Linear Multi-Agent System with Uncertainties and Communication Delays |
|
Wenlong, Yang | Tsinghua University |
Deng, Ruiliang | Tsinghua University |
Zhang, Weixian | Tsinghua University |
Shi, Zongying | Tsinghua University |
Zhong, Yi-Sheng | Tsinghua University |
Keywords: Adaptive control, Distributed robust controller synthesis, Control under communication constraints (nonlinearity)
Abstract: This paper investigates fully distributed robust adaptive formation control problems of a class of general linear higher-order systems subject to heterogeneous uncertainties over a deterministic network under time-varying communication delays. A novel robust adaptive strategy is developed to cope with the uncertainties dependent on control inputs as well as system states. Thereafter, an original fully distributed formation controller is designed, which incorporates two parts, namely, the nominal controller relying on delayed neighbouring information to attain the desired formation and the robust adaptive compensating signal to restrain the influences of uncertainties. The controller design and implementation requires neither the global information about interaction graph nor the upper bounds of uncertainties. Based on the Lyapunov-Krasovskii arguments, sufficient conditions for the closed-loop system in the presence of network latency to achieve the desired formation is derived. Numerical simulation results are presented to demonstrate the effectiveness of the proposed formation protocol.
|
|
13:30-15:30, Paper ThBT2.10 | |
Emergence of Bipartite Flocking Behavior for Cucker-Smale Model in Presence of Lossy Links |
|
Shi, Xiaoyu | School of Electrical Engineering and Electronic Information, Xih |
Ma, Zhuangzhuang | School of Automation Engineering, University of Electronic Scien |
Shi, Lei | University of Electronic Science and Technology of China |
Yang, Yong | Xihua University |
Weicheng, Xie | Xihua University, Chengdu, China |
Keywords: Adaptive control, Robust control, Stability of nonlinear systems
Abstract: This paper investigates the issue of discrete-time bipartite flocking control for Cucker-Smale model subject to cooperation-competition interations and lossy links. The data packets loss from the controller to the actuator are simulated as a Bernoulli distribution process. The cooperation and competition among individuals are described as a signed digraph. Based on the products convergence approach of infinite sub-stochastic matrices, a algebraic condition which is related to initial states, the topological structure and the successful information transmission rate is established, so as to achieve bipartite flocking. At last, the theoretical result is exemplied through numerical simulations.
|
|
13:30-15:30, Paper ThBT2.11 | |
Attitude Tracking Control of Uncertain Flexible Spacecraft Systems Subject to External Disturbances |
|
Bao, Ze An | Beijing Institute of Technology |
Lu, Maobin | Beijing Institute of Technology |
Deng, Fang | Beijing Institute of Technology |
Keywords: Adaptive control, Observer design, Disturbance rejection
Abstract: In this paper, we consider the attitude tracking and disturbance rejection problem of uncertain flexible spacecrafts. Compared with existing works, we consider two types of uncertainties of flexible spacecrafts, that is, the uncertain parameters of the inertial matrix, and the unknown external disturbance with unbounded energy. Inspired by the internal model principle, we design a class of dynamic compensators and some auxiliary dynamic systems to compensate the external disturbance. Then, by introducing a series of coordinate transformations, we convert the attitude tracking and disturbance rejection problem into an adaptive regulation problem of an augmented system. Finally, we design the adaptive control law and show that attitude tracking of uncertain flexible spacecrafts can be achieved in the presence of unknown disturbances. The effectiveness and robustness of the controller are illustrated by some numerical simulations.
|
|
13:30-15:30, Paper ThBT2.12 | |
ASPR-Based Output Feedback Control with Virtual PFC for Output Tracking |
|
Akaike, Kota | Kumamoto University |
Yu, Hao | Beijing Institute of Technology |
Mizumoto, Ikuro | Kumamoto Univ |
Chen, Tongwen | University of Alberta |
Keywords: Adaptive control, Output feedback control (linear case), Regulation (linear case)
Abstract: Nowadays, the output feedback control method based on the Almost Strictly Positive Real (ASPR) property gets many attentions and has been researched widely. ASPR models can be stabilized by applying simple output feedback control; so the designed controllers have a simple structure. However, the systems have to satisfy quite strict conditions in order to obtain ASPR-ness, although almost all practical systems do not have the ASPR property. Therefore, for relaxing those conditions, the introduction of a Parallel Feedforward Compensator (PFC) has been proposed. This method can render the resulting augmented system ASPR. Up to now, several PFC design methods have been proposed, and one of them is an adaptive PFC design scheme. This technique has a feature that it can design a PFC automatically by utilizing online data. Furthermore, for the purpose of output regulation, the control design methods with an adaptive PFC have been proposed. Unfortunately, however, in almost all schemes, the discussion on the convergence of actual errors has not been conducted. Therefore, in this paper, introducing a virtual PFC model and an auxiliary input for ensuring ASPR-ness, a new ASPR-based output feedback control method is proposed, and the stability analysis and convergence of the actual error are discussed. Finally, the effectiveness of the proposed method is confirmed via numerical simulations.
|
|
ThBT3 |
Hall A-3 |
Field and Flying Robots |
Interactive Session |
Chair: Nikolakopoulos, George | Luleå University of Technology |
Co-Chair: Sampei, Mitsuji | Tokyo Inst. of Tech |
|
13:30-15:30, Paper ThBT3.1 | |
Semantic and Topological Mapping Using Intersection Identification |
|
Fredriksson, Scott | Luleå University of Technology |
Saradagi, Akshit | Luleå University of Technology |
Nikolakopoulos, George | Luleå University of Technology |
Keywords: Field robotics, Intelligent robotics, Trajectory and path planning
Abstract: This article presents a novel approach to identifying and classifying intersections for semantic and topological mapping. More specifically, the proposed novel approach has the merit of generating a semantically meaningful map containing intersections, pathways, dead ends, and pathways leading to unexplored frontiers. Furthermore, the resulting semantic map can be used to generate a sparse topological map representation, that can be utilized by robots for global navigation. The proposed solution also introduces a built-in filtering to handle noises in the environment, to remove openings in the map that the robot cannot pass, and to remove small objects to optimize and simplify the overall mapping results. The efficacy of the proposed semantic and topological mapping method is demonstrated over a map of an indoor structured environment that is built from experimental data. The proposed framework, when compared with similar state-of-the-art topological mapping solutions, is able to produce a map with up to 89% fewer nodes than the next best solution.
|
|
13:30-15:30, Paper ThBT3.2 | |
Event Camera and LiDAR Based Human Tracking for Adverse Lighting Conditions in Subterranean Environments |
|
Valdes Saucedo, Mario Alberto | Lulea University of Technology |
Patel, Akash | Luleå University of Technology |
Sawlekar, Rucha | Luleå University of Technology |
Saradagi, Akshit | Luleå University of Technology |
Kanellakis, Christoforos | Luleå University of Technology |
Agha-mohammadi, Ali-akbar | NASA-JPL, Caltech |
Nikolakopoulos, George | Luleå University of Technology |
Keywords: Field robotics, Perception and sensing, Information and sensor fusion
Abstract: In this article, we propose a novel LiDAR and event camera fusion modality for subterranean (SubT) environments for fast and precise object and human detection in a wide variety of adverse lighting conditions, such as low or no light, high-contrast zones and in the presence of blinding light sources. In the proposed approach, information from the event camera and LiDAR are fused to localize a human or an object-of-interest in a robot's local frame. The local detection is then transformed into the inertial frame and used to set references for a Nonlinear Model Predictive Controller (NMPC) for reactive tracking of humans or objects in SubT environments. The proposed novel fusion uses intensity filtering and K-means clustering on the LiDAR point cloud and frequency filtering and connectivity clustering on the events induced in an event camera by the returning LiDAR beams. The centroids of the clusters in the event camera and LiDAR streams are then paired to localize reflective markers present on safety vests and signs in SubT environments. The efficacy of the proposed scheme has been experimentally validated in a real SubT environment (a mine) with a Pioneer 3AT mobile robot. The experimental results show real-time performance for human detection and the NMPC-based controller allows for reactive tracking of a human or object of interest, even in complete darkness.
|
|
13:30-15:30, Paper ThBT3.3 | |
Traversability Aware Graph Based Subterranean Exploration with Unmanned Aerial Vehicles |
|
Patel, Akash | Luleå University of Technology |
Kanellakis, Christoforos | Luleå University of Technology |
Nikolakopoulos, George | Luleå University of Technology |
Agha-mohammadi, Ali-akbar | NASA-JPL, Caltech |
Keywords: Autonomous robotic systems, Flying robots, Robotics technology
Abstract: Subterranean exploration and mapping for search and rescue robotics have become an emerging research direction since the DARPA organized Subterranean Challenge. As part of development efforts within the team CoSTAR (Collaborative SubTerranean Autonomous Robots) in the Sub-T challenge, this work establishes a novel traversable graph-based exploration strategy that utilizes frontiers for local navigation and a fast collision risk-aware graph building for global navigation. The exploration strategy extracts frontiers in an unknown area that contribute to safe navigation while maximizing information gain for the robot. The exploration problem is further bifurcated into local and global exploration for faster decision-making at junctions with the goal of rapidly exploring the area. The local exploration guarantees collision-free straight-line paths to informative frontiers for rapid forward navigation, while global re-positioning utilizes a traversable graph subject to geometrical collision checks within the occupancy map. The pathfinding in a graph is addressed using a heuristic, which combines risk margins and travel costs to assist in short yet safe paths to the global frontier in case of a dead end in local exploration. The presented exploration strategy is developed with the goal of making exploration algorithms platform agnostic in order to be able to use it with aerial, as well as ground robots. The proposed method is also evaluated against different state-of-the-art exploration planners in simulated fixed-time budget-based exploration missions on an Unmanned Aerial Vehicle (UAV) in order to benchmark the capabilities and highlight the novelty.
|
|
13:30-15:30, Paper ThBT3.4 | |
Highly Accurate Obstacle Localization Using Fused Inertial, RTK-GNSS, and Lidar Positioning for Agricultural Field Operations |
|
Lemke, Julian A. I. | Technical University of Munich |
Soitinaho, Riikka | Technical University of Munich |
Oksanen, Timo | Technical University of Munich |
Keywords: Field robotics, Precision agriculture, Perception and sensing
Abstract: Autonomous vehicles need to recognize and localize obstacles in their environment in order to avoid collisions. This paper presents a novel method for estimating the misalignment between a simultaneous localization and mapping (SLAM) map and and an Earth-fixed coordinate systems in order to allow highly accurate global localization of obstacles in the environment. The sensors used for this method are an Inertial Measurement Unit (IMU), satellite-based positioning (GNSS/GPS) and both 2D and 3D lidar sensors. Experimental validation on a tractor shows that the typical global localization accuracy is in the range of 100 mm...150 mm.
|
|
13:30-15:30, Paper ThBT3.5 | |
Detection and Depth Estimation for Domestic Waste in Outdoor Environments by Sensors Fusion |
|
Páez Ubieta, Ignacio de Loyola | University of Alicante |
Velasco Sánchez, Edison Patricio | University of Alicante |
Puente, Santiago T. | University of Alicante |
Candelas Herias, Francisco A. | University of Alicante |
Keywords: Information and sensor fusion, Perception and sensing, Field robotics
Abstract: In this work, we estimate the depth in which domestic waste are located in space from a mobile robot in outdoor scenarios. As we are doing this calculus on a broad range of space (0.3 - 6.0 m), we use RGB-D camera and LiDAR fusion. With this aim and range, we compare several methods such as average, nearest, median and center point, applied to those which are inside a reduced or non-reduced Bounding Box (BB). These BB are obtained from segmentation and detection methods which are representative of these techniques like Yolact, SOLO, You Only Look Once (YOLO)v5, YOLOv6 and YOLOv7. Results shown that, applying a detection method with the average technique and a reduction of BB of 40%, returns the same output as segmenting the object and applying the average method. Indeed, the detection method is faster and lighter in comparison with the segmentation one. The committed median error in the conducted experiments was 0.0298 ± 0.0544 m.
|
|
13:30-15:30, Paper ThBT3.6 | |
Automation and Control Challenges in Fuel Debris Retrieval Operations for Fukushima Daiichi Decommissioning |
|
Sakaue, Tomoki | Tokyo Electric Power Company Holdings, Inc |
Zhang, Kaiqiang | UKAEA |
Abe, Fumiaki | Tokyo Electric Power Company Holdings, Inc |
Sakamoto, Masaki | Tokyo Electric Power Company Holdings, Inc |
Shirai, Shu | Tokyo Electric Power Company Holdings, Inc |
Sato, Wataru | Tokyo Electric Power Company Holdings, Inc |
Sugawara, Yoshimasa | Tokyo Electric Power Company Holdings, Inc |
Plianos, Alexandros | Univ |
Caliskanelli, Ipek | UK Atomic Energy Authority |
Tugal, Harun | Manchester University |
Goodliffe, Matthew | UK Atomic Energy Authority |
Pacheco-Gutierrez, Salvador | UK Atomic Energy Authority |
Skilton, Robert | UK Atomic Energy Authority |
Keywords: Field robotics, Work in real and virtual environments, Robotics technology
Abstract: Fukushima Daiichi decommissioning is a long-term engineering challenge, of which advanced control techniques are essentially demanded. In the past ten years, the success in various decommissioning operations demonstrates the importance of elaborating state-of-the-art control and automation technologies. However, there are still various control engineering issues in the upcoming fuel debris retrieval operations at Fukushima Daiichi. These control issues cannot be resolved by applying existing control techniques or products, because typical control solutions do not need to consider the extreme environmental conditions and highly demanded safety requirements for operations within the post-accident environments therein. This paper and the associated discussions will introduce the automation and control challenges that need to be addressed by the control society. This aims to disseminate these control challenges to academia and industry, and therefore encourage practitioners to collaboratively develop novel solutions for the extreme engineering practice.
|
|
13:30-15:30, Paper ThBT3.7 | |
Stability Focused Evaluation and Tuning of Special Ground Vehicle Tracking Algorithms |
|
Bauer, Peter | Institute for Computer Science and Control |
Nagy, Mihaly | Institute for Computer Science and Control |
Kuna, Gergely István | Institute for Computer Science and Control |
Kisari, Adam | Institute for Computer Science and Control |
Simonyi, Ernő | SZTAKI |
Hiba, Antal | Hungarian Academy of Sciences, Institute for Computer Science An |
Drotár, István | Széchenyi István University |
Keywords: Guidance navigation and control, Flying robots, Autonomous robotic systems
Abstract: This paper deals with a special tracking problem when a ground vehicle should be tracked by a multicopter flying ahead of the vehicle. Pre-designed vehicle route is assumed and the UAV stops or slows down at every intersection to react to route changes. After introducing the problem, the methods applied in a real flight demonstration in the Smart City module of ZalaZONE proving ground are presented. Then new methods are introduced to possibly improve performance. The main focus of the article is the evaluation of the stability of the methods and the provision of tuning guidelines. All of the introduced methods is tuned based-on the guidelines considering real ground vehicle test data and the high fidelity simulation of the applied multicopter. The two best methods are compared in detail and guidelines of their applicability are provided.
|
|
13:30-15:30, Paper ThBT3.8 | |
Control of Convertible UAV with Vectorized Thrust |
|
Lopes de Oliveira, Tomas | Universite Cote d'Azur - I3S |
Anglade, André | Laboratoire I3S UMR 7271 UCA-CNRS |
Hamel, Tarek | Université Côte D'Azur |
Samson, Claude | INRIA/CNRS/Univ. Nice Sophia-Antipolis |
Keywords: Guidance navigation and control, Flying robots, Aerospace
Abstract: This paper is an addition to an article previously published by three of the authors that addresses the control of convertible fixed-wing aircraft with vectorized thrust. The control solution here developed extends the one presented in the former paper by complementing it with a strategy for the hovering flight and a control policy to handle the transition phase between low and high airspeed. An estimator of the air velocity required in all flight phases is also proposed. Realistic simulation results on a tri-tilt rotor Unmanned Aerial Vehicle (UAV) illustrate and assess the methodology.
|
|
13:30-15:30, Paper ThBT3.9 | |
Optimization of Rotor Arrangement for a Multirotor UAV with Robustness against a Single Rotor-Failure |
|
Mochida, Shunsuke | Tokyo Institute of Technology |
Terunuma, Reiji | Tokyo Institute of Technology |
Ito, Takumi | Tokyo Institute of Technology |
Funada, Riku | Tokyo Institute of Technology |
Ibuki, Tatsuya | Meiji University |
Sampei, Mitsuji | Tokyo Inst. of Tech |
Keywords: Flying robots, Design methodologies, System analysis and optimization
Abstract: This paper proposes the optimization scheme for designing rotor arrangements for a multirotor unmanned aerial vehicle (UAV), which achieves high manipulability with satisfying fault-tolerant properties against an arbitrary single rotor fault. The proposed optimization problem is formulated to yield UAVs in which rotors are all directed upward and arranged on the same plane without overlapping. We then apply this optimization problem to design a hexarotor. The obtained structure shows a similar structure to the 2Y hexarotor, which was presented in the previous work without guaranteeing its optimality. We then build a prototype of the 2Y hexarotor. The experimental demonstration verifies the robustness of the 2Y hexarotor against any single rotor malfunction.
|
|
13:30-15:30, Paper ThBT3.10 | |
Anti-Disturbance Trajectory Tracking Control for a Quadrotor UAV with Input Constraints |
|
Hongjiao Niu, Hongjiao | Peking University |
Keywords: Flying robots, Motion control systems, Control of systems in vehicles
Abstract: This paper presents the trajectory tracking control for a quadrotor unmanned aerial vehicle(UAV) with disturbances and input constraints. The UAV's system is decomposed into an outer position loop and an inner attitude loop. The position tracking control is achieved by a class of saturated proportional-derivative(PD) control laws. Assuming that the unknown disturbances mainly effect on the translational dynamics, an adaptive control term is investigated to compensate the effects of the disturbances. The position tracking control force implies a coupled-attitude system that connects the inner attitude loop with the outer position loop. An intrinsic PD control law, which is directly designed on the special orthogonal group SO(3), is proposed to track the desired attitude. In order to reduce the calculation difficulty of the attitude tracking control law, an observer-based control law is further developed while the control law and observer can be designed separately. Simulation results complete this work.
|
|
13:30-15:30, Paper ThBT3.11 | |
Automatic Threshold Temperature Assessment for Sweet Pepper Detection Using Far-Infrared Camera |
|
Tasneem, Zinat | Kochi University of Technology |
Tada, Naoya | Kochi University of Technology |
Oka, Koichi | Kochi University of Technology |
Keywords: Field robotics, Intelligent robotics, Perception and sensing
Abstract: Fruit detection is a critical function in the field of agricultural robotics. The researchers have used various methods to precisely pinpoint the location of the fruit. This study identified sweet peppers in Kochi Prefecture, Japan, using a thermal recognition-based method. The obtained images were assessed and then used as inputs for a machine-learning system based on supervised categorization by applying an image processing technique. By automatically detecting the threshold temperature range employing artificial intelligence, it is proposed that the estimation result can be enhanced to some degree. The algorithms Bagging and K-Nearest Neighbourhood (KNN) were employed for this estimation. The harmonic average of recall and precision, otherwise known as the F value, is shown to have been within 30 to 40 percent on most occasions. Additionally, in certain instances, the KNN outperformed the F-value. The F-value for bagging hardly ever rises above 70%, but with KNN, it occasionally rises beyond 80%. As a result, it can be said that the detection method for automatically determining the temperature threshold is efficient for detecting sweet peppers
|
|
13:30-15:30, Paper ThBT3.12 | |
Nano Quadcopter Obstacle Avoidance with a Lightweight Monocular Depth Network |
|
Liu, Cheng | Delft University of Technology |
Xu, Yingfu | Delft University of Technology |
van Kampen, Erik-Jan | Delft University of Technology |
De Croon, Guido | TU Delft |
Keywords: Autonomous robotic systems, Perception and sensing, Flying robots
Abstract: In this paper, we propose an obstacle avoidance solution for a 34-gram quadcopter equipped with a monocular camera. The perception of obstacles is tackled by a lightweight convolutional neural network predicting a dense depth map from a captured grey-scale image. The depth network performs self-supervised learning and thus requires no ground-truth labels that are costly to acquire. Based on the depth map, the control strategy is implemented by a behavior state machine that balances the efficiency to explore the environment and the safety of avoiding obstacles. In real-world flight experiments, our solution demonstrates the efficacy of predicting trust-worthy depth maps and a stable control strategy in various cluttered environments.
|
|
ThC02 |
Room 301 |
Data-Driven Methods in Social Systems |
Regular Session |
Chair: Hsieh, Chung-Han | National Tsing Hua University |
Co-Chair: Belgioioso, Giuseppe | ETH Zürich |
|
16:00-16:20, Paper ThC02.1 | |
Continuous-Time Modeling of Financial Returns Based on Limit Order Book Data |
|
Busetto, Riccardo | Politecnico Di Milano |
Formentin, Simone | Politecnico Di Milano |
Keywords: Financial systems, Continuous time system estimation, Machine learning
Abstract: The Limit Order Book (LOB) of a financial security contains the list of buy and sell orders placed by traders on a single or across many exchanges for a given stock. As such, the amount of information contained in the LOB is much richer than that contained in the time history of the mean price, so it can potentially be exploited to model and predict more accurately the future returns. As far as we are aware, this work offers - for the first time - a dynamical systems perspective on the latter modeling problem, leading to a two-fold contribution: (i) we will define a new regressor, called Base Imbalance, and we will show that its predictive potential is more significant than the ones usually employed in the literature; (ii) we will discuss that the most suitable way to derive a model of the LOB dynamics is via continuous-time system identification, due to the event-based nature of the phenomenon at hand. The effectiveness of the proposed modeling strategy to be used in trading policies will be illustrated by means of a benchmark experimental data.
|
|
16:20-16:40, Paper ThC02.2 | |
On Data-Driven Drawdown Control with Restart Mechanism in Trading |
|
Hsieh, Chung-Han | National Tsing Hua University |
Keywords: Control in economics, Data-driven decision making, Financial systems
Abstract: This paper extends the existing drawdown modulation control policy to include a novel restart mechanism for trading. It is known that the drawdown modulation policy guarantees the maximum percentage drawdown no larger than a prespecified drawdown limit for all time with probability one. However, when the prespecified limit is approaching in practice, such a modulation policy becomes a stop-loss order, which may miss the profitable follow- up opportunities, if any. Motivated by this, we add a data-driven restart mechanism into the drawdown modulation trading system to auto-tune the performance. We find that with the restart mechanism, our policy may achieve a superior trading performance to that without the restart, even with a nonzero transaction costs setting. To support our findings, some empirical studies using equity ETF and cryptocurrency with historical price data are provided.
|
|
16:40-17:00, Paper ThC02.3 | |
Data-Driven Behaviour Estimation in Parametric Games |
|
Anna Maria, Maddux | EPFL |
Pagan, Nicolò | University of Zürich |
Belgioioso, Giuseppe | ETH Zürich |
Dorfler, Florian | Swiss Federal Institute of Technology (ETH) Zurich |
Keywords: Game theories, Data-driven decision making
Abstract: A central question in multi-agent strategic games deals with learning the underlying utilities driving the agents' behaviour. Motivated by the increasing availability of large datasets, we develop an unifying data-driven technique to estimate agents' utility functions from their observed behaviour, irrespective of whether the observations correspond to equilibrium configurations or to temporal sequences of action profiles. Under standard assumptions on the parametrization of the utilities, the proposed inference method is computationally efficient and finds all the parameters that rationalize the observed behaviour best. We numerically validate our theoretical findings on the market share estimation problem under advertising competition, using historical data from the Coca-Cola Company and Pepsi Inc. duopoly.
|
|
17:00-17:20, Paper ThC02.4 | |
Decision-Focused Learning for Inverse Noncooperative Games: Generalization Bounds and Convergence Analysis |
|
Al-Tawaha, Ahmad | Virginia Tech |
Kaushik, Harshal | Virginia Tech |
Sel, Bilgehan | Virginia Tech |
Jia, Ruoxi | Virginia Tech |
Jin, Ming | Virginia Tech |
Keywords: Data-driven decision making, Game theories, Machine learning
Abstract: Finding the equilibrium strategy of agents is one of the central problems in game theory. Perhaps equally intriguing is the inverse of the above problem: from the available finite set of actions at equilibrium, how can we learn the utilities of players competing against each other and eventually use the learned models to predict their future actions? Instead of following an estimate-then-predict approach, this work proposes a decision-focused learning (DFL) method that directly learns the utility function to improve prediction accuracy. The game's equilibrium is represented as a layer and integrated into an end-to-end optimization framework. We discuss the statistical bounds of covering numbers for the set of solution functions corresponding to the solution of a generic parametric variational inequality. Also, we establish the generalization bound for the set of solution functions with respect to the smooth loss function with an improved rate. Moreover, we proposed an algorithm based on the iterative differentiation strategy to forward and backpropagate through the equilibrium layer. The convergence analysis of the proposed algorithm is established. Finally, We numerically validate the proposed framework in the utility learning problem among the agents whose utility functions are approximated by partially input convex neural networks (PICNN).
|
|
17:20-17:40, Paper ThC02.5 | |
Price Dynamics in the Oil Market: A Bond-Graph Modeling Approach |
|
Hutters, Coenraad | Delft University of Technology |
Orie, Nicolaas | Shell |
Mendel, Max | TU Delft |
Keywords: Financial systems, Business and financial analytics, Grey box modelling
Abstract: Current oil modeling techniques lack a comprehensive approach, as long-term oil prices are qualitatively modeled based on first principles, while short-term price transients are modeled using econometric methods. In this paper we propose a comprehensive bond-graph modeling approach in which price dynamics follow from first principles. The first principles that we use are derived from the recently developed economic-engineering theory in which price dynamics are modeled using Newtonian mechanics and price drivers are identified as forces. We reformulate a qualitative first-principles model developed by the Energy Information Administration (EIA) as a bond graph by modeling six identified price-driving factors as port-elements. The constitutive laws of these port-elements generate the price drivers, which through the interconnection structure of the bond graph yield the price dynamics. We demonstrate the bond-graph model by identifying its parameters and letting it estimate the oil price given historic oil supply data. Compared to a benchmark black-box model, we find that the bond graph has two advantages: (i) it achieves a better performance, and (ii) we know what its parameters and variables represent. The latter advantage allows us to validate the bond-graph model by reconstructing the oil inventory stocks and to manually adjust parameters by expert input.
|
|
ThC03 |
Room 302 |
Mechatronics Tools and Control Related to Robotic Manipulation |
Open Invited Session |
Chair: Benoussaad, Mourad | INP-ENIT, University of Toulouse |
Co-Chair: Mauze, Benjamin | ENIT, Unversity of Toulouse |
Organizer: Mauze, Benjamin | ENIT, Unversity of Toulouse |
Organizer: Benoussaad, Mourad | INP-ENIT, University of Toulouse |
Organizer: Rakotondrabe, Micky | University of Toulouse |
|
16:00-16:20, Paper ThC03.1 | |
Level Position and Obstacle Avoidance Control for Human-Robot Co-Manipulation of a Rigid Object (I) |
|
Flores, Alejandro | Center for Research in Optics |
Benoussaad, Mourad | INP-ENIT, University of Toulouse |
Flores, Gerardo | Center for Research in Optics |
Rakotondrabe, Micky | University of Toulouse |
Keywords: Robots manipulators, Guidance navigation and control, Human operator support
Abstract: In this paper, velocity control is designed for a robotic arm to assist a human while holding and manipulating a rigid body. The principal tasks of the robot manipulator are: to keep in a level position the held object and to avoid obstacles during its manipulation. Due to the human-robot collaboration, the movement of the robot manipulator is constrained so that the robot's motion does not perturb the human arm. The proposed velocity and obstacle avoidance controller is based on the potential field that contains attractive and repulsive forces. Simulation results show that with the proposed control, the robotic arm can position the held object and avoid near obstacles without disturbing the human arm.
|
|
16:20-16:40, Paper ThC03.2 | |
Micro-Defect Inspection on Curved Surface Using a 6-DOF Robot Arm with One-Shot BRDF Imaging (I) |
|
Oaki, Junji | Toshiba Corporation |
Sugiyama, Nobukatsu | Toshiba Corporation |
Ishihara, Yoshiyuki | Toshiba Corporation |
Ooga, Junichiro | Toshiba Corporation |
Kano, Hiroya | Toshiba Corporation |
Ohno, Hiroshi | Toshiba Corporation |
Keywords: Robots manipulators, Motion control systems, Application of mechatronic principles
Abstract: The need for automated visual inspection in Japan is increasing due to labor shortages caused by the declining birthrate and aging population. We have developed an imaging system called One-shot BRDF (Bidirectional Reflectance Distribution Function), which can easily detect even micro defects that are conventionally difficult to capture using parallel-beam illumination and an image sensor. By colorcoding the direction of light, micro-defects can be instantly captured as a clear image. This paper proposes a novel micro-defect inspection system capable of automatically inspecting the surface of materials with complex shapes by mounting One-shot BRDF optics on the tip of a 6-degree-of-freedom (DOF) robot arm and scanning the material’s surface. The 6-DOF robot arm can track the scanning trajectory and keep the optics squarely against the curved surface at a constant distance. We developed a simple algorithm to automatically determine the trajectory from the material's 3D CAD data so that the entire surface to be scanned can be inspected quickly and within the 6-DOF robot arm’s range of movement. For high-speed and high-precision inspection, we built a nonlinear dynamic model of the 6-DOF robot arm and model-based control to track the trajectory while suppressing vibration. In scanning experiments using mirror-finished aluminum with a curved surface, the position and orientation control errors were sufficiently small in high-speed operation at the limit of the robot arm’s performance. Several minute scratches on the mirror-finished aluminum could be detected and their locations were mapped as 3D CAD data.
|
|
16:40-17:00, Paper ThC03.3 | |
Vibration Free Flexible Object Handling with a Robot Manipulator Using Learning Control (I) |
|
Ronzani, Daniele | KU Leuven |
Mamedov, Shamil | Innopolis University |
Swevers, Jan | KU Leuven R&D |
Keywords: Vibration control, Robots manipulators, Identification and control methods
Abstract: Many industries extensively use flexible materials. Effective approaches for handling flexible objects with a robot manipulator must address residual vibrations. Existing solutions rely on complex models, use additional instrumentation for sensing the vibrations, or do not exploit the repetitive nature of most industrial tasks. This paper develops an iterative learning control approach that jointly learns model parameters and residual dynamics using only the interoceptive sensors of the robot. The learned model is subsequently utilized to design optimal ac{PTP} trajectories that accounts for residual vibration, nonlinear kinematics of the manipulator and joint limits. We experimentally show that the proposed approach reduces the residual vibrations by an order of magnitude compared with optimal vibration suppression using the analytical model and threefold compared with the available state-of-the-art method. These results demonstrate that effective handling of a flexible object does not require neither complex models nor additional instrumentation.
|
|
17:00-17:20, Paper ThC03.4 | |
Comparative Discussion on Two Robust Control Techniques for Piezoelectric Actuators in Manipulation (I) |
|
Khadraoui, Sofiane | University of Sharjah |
Rakotondrabe, Micky | University of Toulouse |
Keywords: Identification and control methods, Micro and nano mechatronic Systems, Modeling
Abstract: One of the applications of piezoelectric actuators (piezoactuators) is high precision manipulation. However, the creep and hysteresis nonlinearities as well as the badly damped dynamics of those actuators make challenging their control to ensure prescribed specifications for the manipulation tasks. Their modeling and control are thus well documented in the literature. This discussion paper considers two recently published control techniques of piezoactuators and provides a comparison and discussions regarding their performance, pros and cons.
|
|
17:20-17:40, Paper ThC03.5 | |
Towards New Type of Shape Memory Alloy Actuators Based Exoskeletons for Assisted Manipulation (I) |
|
Mauze, Benjamin | ENIT, Unversity of Toulouse |
Rakotondrabe, Micky | University of Toulouse |
Keywords: Assistive technology and rehabilitation engineering, Human-centred automation and design, Mechatronic systems
Abstract: In the Industry 5.0, human will work assisted by technologies to gain better efficiency and working conditions. Exoskeletons represent appealing solutions to reduce working musculoskeletal disorders. However, current devices suffer from their rigidity and their lack of adaptability. In this paper, we propose a new concept of exoskeleton composed of shape memory alloy (SMA) actuators of several forms. The objective is to design a more versatile and personalized assistive exoskeleton with a better acceptance rate. After describing the proposed equipment, its model and control strategies are discussed considering the shape-changing effect of the material to get a comfortable, accurate, and helpful device.
|
|
17:40-18:00, Paper ThC03.6 | |
Sensitivity Analysis in Self-Assembly Self-Repair System |
|
Caballero, Renzo | King Abdullah University of Science and Technology |
Feron, Eric | Georgia Tech |
Keywords: Modeling, Robotics, Mechatronic systems
Abstract: We study a case of robot interaction where a robot arm partially repairs a 3D printer by adjusting one of the support columns in the structure of the 3D printer. The collaboration stability is challenged when we assume that the robot misplaced the column on the 3D printer, leading to a non-ideal 3D printer and compromising the quality of the printing process. Experiments are conducted to find and analyze the limits in which the system can maintain self-repair and self-assemble. Based on observations, we constructed and validated mathematical models to explain the results of the experiment and analyze the stability of the self-repair process.
|
|
ThC04 |
Room 303 |
Aerospace |
Regular Session |
Chair: Ikeda, Yuichi | Shonan Institute of Technology |
Co-Chair: Sato, Masayuki | Kumamoto University |
|
16:00-16:20, Paper ThC04.1 | |
LPV Three-Loop Autopilot Using Dynamic Inversion: A Practical Approach |
|
Rajput, Jahanzeb | Centers of Excellence in Science and Applied Technologies, Islam |
Khan, Hafiz Zeeshan Iqbal | Centers of Excellence in Science and Applied Technologies, Islam |
Keywords: Aerospace, Parameter-varying systems, Structural properties
Abstract: This work presents a linear parameter varying (LPV) three-loop longitudinal autopilot that is derived using the dynamic inversion technique. The conventional three-loop autopilots are traditionally designed at various flight conditions using linearized models and are then scheduled as a function of several parameters such as Mach number, velocity, angle-of-attack, etc., which remains a challenging and time-consuming task till today. In contrast, the proposed three-loop autopilot embeds the parameterized gains, from which the parameterized gain-multipliers are directly obtained in the form of explicit formulae. Exploiting the utility of the proposed autopilot structure, a design methodology for LPV controller design is presented, in which, a linear three-loop autopilot designed at single flight condition can be transformed into an LPV autopilot using the derived parameterized gain-multipliers. Simulation results are also presented to demonstrate the performance of the proposed technique.
|
|
16:20-16:40, Paper ThC04.2 | |
Autonomous Satellite Rendezvous and Proximity Operations with Time-Constrained Sub-Optimal Model Predictive Control |
|
Behrendt, Gabriel | University of Florida |
Soderlund, Alexander | Air Force Research Lab |
Hale, Matthew | University of Florida |
Phillips, Sean | Air Force Research Laboratory |
Keywords: Aerospace, Real-time optimal control, Autonomous systems
Abstract: This paper presents a time-constrained model predictive control strategy for the 6 degree-of-freedom (6DOF) autonomous rendezvous and docking problem between a controllable “deputy” spacecraft and an uncontrollable “chief” spacecraft. The control strategy accounts for computational time constraints due to limited onboard processing speed. The translational dynamics model is derived from the Clohessy-Wiltshire equations and the angular dynamics are modeled on gas jet actuation about the deputy’s center of mass. Simulation results are shown to achieve the docking configuration under computational time constraints by limiting the number of allowed algorithm iterations when computing each input. Specifically, we show that upwards of 90% of computations can be eliminated from a model predictive control implementation without significantly harming control performance.
|
|
16:40-17:00, Paper ThC04.3 | |
Predictive Control for Large Angle Attitude Tracking Maneuver of Spacecraft with Reaction Control System and Reaction Wheel |
|
Ikeda, Yuichi | Shonan Institute of Technology |
Takaku, Yuichi | Tokyo Univercity of Science |
Keywords: Aerospace, Nonlinear predictive control
Abstract: Missions involving rapid and large angle attitude maneuvers have been conceived in astronomical and earth observation satellites in recent years. As an actuator capable of generating a large torque is also going to be required, it will also be necessary to consider characteristics of an actuator in designing a control system. Actuators capable of generating a large torque include reaction control system (RCS). RCS gives an on/off input as it uses the reaction force from fuel injection by thrusters, it can generate a large moment. In addition, the control system of current application satellites normally uses both RCS and reaction wheel (RW) conventionally used for attitude control. This paper considers large angle attitude maneuver of spacecraft by a combination of RCS and RW. To this end, characteristics of RCS and RW are defined, and a discrete-time model (Euler approximation model) for the control system design is derived. Next, we design a discrete-time nonlinear tracking controller so that the closed-loop system consisting of the Euler approximation model becomes input-to-state stable (ISS) using the concept of backstepping approach. Then, we propose a method to appropriately change the threshold of RCS injection corresponding to the attitude of spacecraft by model predictive control. Finally, the effectiveness of proposed control method is verified by numerical simulations
|
|
17:00-17:20, Paper ThC04.4 | |
On Distributed Optimal Control of Satellite Constellation Separation with Differential Drag |
|
Asakura, Hibiki | Kyoto University |
Fujimoto, Kenji | Kyoto University |
Maruta, Ichiro | Kyoto University |
Izui, Kazuhiro | Kyoto University |
Shima, Takeya | Mitsubishi Electric Corporation, Advanced Technology R&D Center |
Honda, Akihiko | Mitsubishi Electric Corporation |
Noro, Takumi | Mitsubishi Electric Corporation |
Yoshikawa, Shoji | Advanced Technology R&D Center, Mitsubishi Electric |
Imagi, Akihiko | Mitsubishi Electric Corporation |
Keywords: Decentralized control, Aerospace, Optimal control of partial differential equations
Abstract: In this paper, we propose an approximately optimal autonomous decentralized control law for satellite constellation separation using differential drag. The problem to be solved is to find an optimal control for minimizing altitude loss. With conventional methods, this can only be solved numerically. However, we show that one can obtain an analytical solution for the ideal constellation separation problem. We then construct a two-degree-of-freedom distributed controller based on this solution. This controller can be used regardless of the number of satellites. Our numerical simulation demonstrates the effectiveness of the proposed method.
|
|
17:20-17:40, Paper ThC04.5 | |
Minimizing Look Angle Rate Guidance Law Considering Impact Angle and Field-Of-View Limit |
|
Lee, Youngjun | Seoul National University |
Kim, Youdan | Seoul National University |
Keywords: Aerospace, Optimal control theory, Analytic design
Abstract: This study proposes a look angle rate minimizing optimal guidance law with impact angle control and look angle limit. The optimal control theory is adopted to solve the look angle rate minimization problem which has the state inequality on the look angle limit and constraint for impact angle control at the final time. The performance of the proposed guidance law is shown demonstrated by simulations for engagement scenarios of several look angle limits and impact angle constraints. The comparative study shows that the proposed guidance law outperforms on the energy and look angle managing ability.
|
|
ThC05 |
Room 304 |
Predictive Control III |
Regular Session |
Chair: Suzuki, Masayasu | Utsunomiya University |
Co-Chair: Kolmanovsky, Ilya V. | University of Michigan |
|
16:00-16:20, Paper ThC05.1 | |
Robust Model Predictive Control for Linear Sampled-Data Systems with Irregular Sampling Times |
|
Buschermöhle, Philipp | Leibniz Universität Hannover |
Lilge, Torsten | Leibniz Universitat Hannover |
Muller, Matthias A. | Leibniz University Hannover |
Keywords: Predictive control, Sampled-data control
Abstract: This paper presents a sampled-data tube-based robust MPC scheme for linear continuous-time systems with irregular sampling times. The sampled-data control law is updated only at discrete sampling instances, but the proposed controller guarantees constraint satisfaction of the continuous-time state for all times. The proposed MPC scheme allows for two sources of uncertainty, (i) uncertain sampling times and (ii) an additional disturbance to the continuous-time system. A constraint adaptation is presented to handle this setting in a rigid tube MPC framework. Constraint satisfaction and convergence of the continuous-time state are shown for the proposed MPC scheme.
|
|
16:20-16:40, Paper ThC05.2 | |
Lifted Bilinear Model-Based Linear Model Predictive Control with Scalability |
|
Kanai, Masaki | Hitachi, Ltd |
Yamakita, Masaki | Tokyo Inst. of Tech |
Keywords: Predictive control, Real-time optimal control, Industrial applications of optimal control
Abstract: We propose a novel linear model predictive control (MPC) using a lifted bilinear model based on Koopman theory, which is computationally scalable against the dimension of the target system and the prediction horizon length. In MPC, the accuracy of the prediction model determines control performance, but it is a challenge to reduce the computational cost especially when considering nonlinearity of the model. To address this, a method has been proposed which represents the nonlinear input affine system as a lifted bilinear model and utilizes linear approximation and prediction error correction regarding the lifted state to achieve a low-computational-cost linear MPC with equivalent performance to nonlinear MPC. However, although the previous studies have shown its effectiveness for relatively low-order systems, it has not been applied to practical systems with higher dimensions. In this study, we extend the conventional method and propose a scalable linear MPC using a lifted bilinear model and apply it to higher-order nonlinear systems. In this paper, a quadrotor system operating in three-dimensional space is considered and its analytical lifted bilinear model is derived. In the formulation of linear MPC using the lifted bilinear model, an error correction method is newly introduced to feedback error for adjustment of the numerical relationships among the elements in the lifted state. The effectiveness of the proposed method is demonstrated through numerical simulations.
|
|
16:40-17:00, Paper ThC05.3 | |
Optimal Sub-References for Setpoint Tracking: A Multi-Level MPC Approach |
|
Sun, Dingshan | Delft University of Technology |
Jamshidnejad, Anahita | Delft University of Technology |
De Schutter, Bart | Delft University of Technology |
Keywords: Predictive control, Tracking
Abstract: We propose a novel method to improve the convergence performance of model predictive control (MPC) for setpoint tracking, by introducing sub-references within a multi-level MPC structure. In some cases, MPC is implemented with a short prediction horizon due to limited on-line computation capacity, which could lead to deteriorated dynamic performance. The introduced multi-level optimization method can generate proper sub-references for the MPC setpoint tracking problem, and efficiently improve the dynamic performance. In the higher level a specific performance criterion is taken as the objective, while explicit MPC is utilized in the lower level to represent the control input. The generated sub-references are then used in MPC for the real system with prediction horizon restrictions. Setpoint-tracking MPC for linear systems is used to illustrate the approach throughout the paper. Numerical simulations show that MPC with sub-references significantly improves the convergence performance compared with regular MPC with the same prediction horizon. Thus, it can be concluded that MPC with sub-references has a high potential to tackle more complicated control problems with limited computation capacity.
|
|
17:00-17:20, Paper ThC05.4 | |
Model Predictive Control of Street Lighting Based on Spatial Points of Interest |
|
Shaheen, Husam I | University of Zagreb Faculty of Electrical Engineering and Compu |
Gapit, Marina | University of Zagreb Faculty of Electrical Engineering and Compu |
Gireesan, Sruthy | University of Zagreb Faculty of Electrical Engineering and Compu |
Lesic, Vinko | University of Zagreb Faculty of Electrical Engineering AndComput |
Keywords: Predictive control, Convex optimization, Tracking
Abstract: The paper focuses on achieving optimal operation of the street lighting by adjusting light intensities of the luminaires according to the surrounding environment. The control system objective is to simultaneously maintain desired level of comfort visibility for vehicles, pedestrians, cyclists, etc. and minimize the energy consumption. Spatial points of interest are chosen and the street dimming scenario is modified to ensure required lighting of the critical ones, while reference values are calculated based on the predicted road and weather conditions. Based on the mathematical model of several neighbouring lamps propagating light to points of interest, a model predictive control algorithm is used to deliver optimal luminous intensity as a trade-off between trajectory tracking problem and energy efficiency. The proposed model is verified by simulations on a real street case study. The results obtained indicate that the algorithm track the reference of different points of interest with set priority.
|
|
17:20-17:40, Paper ThC05.5 | |
A Construction-Free Coordinate-Descent Augmented-Lagrangian Method for Embedded Linear MPC Based on ARX Models |
|
Wu, Liang | Scuola IMT Alti Studi Lucca |
Bemporad, Alberto | IMT Institute for Advanced Studies Lucca |
Keywords: Predictive control, Numerical methods for optimal control, Linear multivariable systems
Abstract: This paper proposes a construction-free algorithm for solving linear MPC problems based on autoregressive with exogenous terms (ARX) input-output models. The solution algorithm relies on a coordinate-descent augmented Lagrangian (CDAL) method previously proposed by the authors, which we adapt here to exploit the special structure of ARX-based MPC. The CDAL-ARX algorithm enjoys the construction-free feature, in that it avoids explicitly constructing the quadratic programming (QP) problem associated with MPC, which would eliminate construction cost when the ARX model changes/adapts online. For example, the ARX model parameters are dependent on linear parameter-varying (LPV) scheduling signals, or recursively adapted from streaming input-output data with cheap computation cost, which make the ARX model widely used in adaptive control. Moreover, the implementation of the resulting CDAL-ARX algorithm is matrix-free and library-free, and hence amenable for deployment in industrial embedded platforms. We show the efficiency of CDAL-ARX in two numerical examples, also in comparison with MPC implementations based on other general-purpose quadratic programming solvers.
|
|
17:40-18:00, Paper ThC05.6 | |
Time-Distributed Optimization for Shrinking Horizon MPC |
|
Leung, Jordan | University of Michigan |
Kolmanovsky, Ilya V. | University of Michigan |
Keywords: Predictive control, Numerical methods for optimal control, Constrained control
Abstract: This paper proposes a strategy for implementing shrinking horizon Model Predictive Control (MPC) using a limited number of optimization iterations at each timestep. Offline and online certification methods are presented for determining a time-varying bound on the number of optimization iterations that ensures the closed-loop system satisfies a specified terminal constraint. An axisymmetric spacecraft spin stabilization example is reported to demonstrate the certification procedure.
|
|
ThC06 |
Room 311 |
Set-Valued Approaches to Control and Estimation of Uncertain Systems II |
Open Invited Session |
Chair: Rauh, Andreas | Carl Von Ossietzky Universität Oldenburg |
Co-Chair: Yong, Sze Zheng | Northeastern University |
Organizer: Dinh, Thach Ngoc | Conservatoire National Des Arts Et Métiers |
Organizer: Rauh, Andreas | Carl Von Ossietzky Universität Oldenburg |
Organizer: Yong, Sze Zheng | Northeastern University |
Organizer: Wang, Zhenhua | Harbin Institute of Technology |
|
16:00-16:20, Paper ThC06.1 | |
Safety Monitoring and Alert for Neural Network-Enabled Control Systems (I) |
|
Lan, Jianglin | University of Glasgow |
Keywords: Observer design, Robust estimation, Diagnosis
Abstract: This paper considers the safety monitoring and enhancement for neural network-enabled control systems with disturbance and measurement noise. A robustly stable interval observer is designed to generate sound lower and upper bounds of the system state. The obtained interval is used to monitor the runtime system state and predict the one-step ahead future system trajectory, providing system safety monitoring and alert. The simulation results of a numerical example and an adaptive cruise control system demonstrate efficacy of the observer in runtime system monitoring and its potentials in detecting sensor faults and enhancing system safety.
|
|
16:20-16:40, Paper ThC06.2 | |
Zonotopic Set-Membership State Estimation for Switched LPV Systems (I) |
|
Zhang, Shuang | Upc |
Puig, Vicenç | Universitat Politècnica De Catalunya (UPC) |
Ifqir, Sara | CRIStAL Lab, Centrale Lille Institute |
Keywords: Observer design, Robust estimation, Uncertain systems
Abstract: This paper addresses the state estimation problem for switched discrete-time Linear Parameter Varying (LPV) systems with mensurable and unmeasurable scheduling parameters. A zonotopic switched polytopic state estimator, considering parameter uncertainty, is proposed based on a Set-Membership Approach (SMA). Taking Average Dwell Time (ADT) into account, a new criterion is proposed to guarantee the convergence of the estimation. An application to vehicle lateral dynamics state estimation is used as case study. Simulation results reveal the effectiveness of the proposed algorithm and demonstrate advantages over the existing methods.
|
|
16:40-17:00, Paper ThC06.3 | |
Active Model Discrimination for Piecewise Affine Inclusion Systems (I) |
|
Niu, Ruochen | Arizona State University |
Gah, Elikplim | Northeastern University |
Yong, Sze Zheng | Northeastern University |
Keywords: Model validation, Control problems under conflict and/or uncertainties, Robust estimation
Abstract: This paper proposes a novel set-membership active model discrimination (AMD) algorithm for actively separating/discriminating among a set of piecewise affine inclusion systems with bounded noise. Specifically, to overcome the difficulties of dealing the integer variables in the lower/inner level of the associated bilevel optimization problem that stem from the mapping of the piecewise inclusions and subregions, we propose an alternative reformulation that moves the integer variables into the higher/outer level. This reformulation allows us to leverage Karush-Kuhn-Tucker (KKT) conditions to obtain an equivalent single level mixed-integer linear programming (MILP) problem. Moreover, in contrast to standard AMD algorithms that strictly enforces model separation, we propose a slight modification/extension that separates as many models as possible when a strict separation of all models is not possible.
|
|
17:00-17:20, Paper ThC06.4 | |
Zonotope-Based Fault Estimation for Uncertain Discrete-Time Switched Linear Systems (I) |
|
Dadi, Leila | University of Gabes |
Dinh, Thach Ngoc | Conservatoire National Des Arts Et Métiers |
Lamouchi, Rihab | Conservatoire National Des Arts Et Métiers (Cnam) |
Ethabet, Haifa | Research Laboratory Modeling, Analysis and Control of Systems ( |
Raïssi, Tarek | Conservatoire National Des Arts Et Métiers |
Aoun, Mohamed | Bordeaux 1 |
Keywords: Observer design, Uncertain systems, Robust estimation
Abstract: This paper investigates actuator fault estimation for discrete-time switched linear systems subject to unknown but bounded disturbances and measurement noises. By taking the fault as an auxiliary state vector, the proposed method consists of two steps. First, a switched L_infty-based descriptor observer attenuating the effect of uncertainties is designed to obtain simultaneous point estimate of the system state and the fault term. Second, interval estimation is achieved by integrating robust point estimation with zonotopic analysis techniques. The observer gains are calculated by solving Linear Matrix Inequality (LMI) derived using a common Lyapunov function. Finally, the effectiveness of the proposed approach is demonstrated through a numerical example.
|
|
17:20-17:40, Paper ThC06.5 | |
Exact Set-Valued Estimation Using Constrained Convex Generators for Uncertain Linear Systems |
|
Silvestre, Daniel | NOVA University of Lisbon , ISR |
Keywords: Observers for linear systems, Parameter-varying systems, Guidance navigation and control
Abstract: Set-valued state estimation when in the presence of uncertainties in the model have been addressed in the literature essentially following three main approaches: i) interval arithmetic of the uncertain dynamics with the estimates; ii) factorizing the uncertainty into matrices with unity rank; and, iii) performing the convex hull for the vertices of the uncertainty space. Approach i) and ii) introduce a lot of conservatism because both disregard the relationship of the parameters with the entries of the dynamics matrix. On the other hand, approach iii) has a large growth on the number of variables required to represent the set or is approximated losing its main advantage in comparison with i) and ii). In this paper, with the application of autonomous vehicles in GPS-denied areas that resort to beacon signals for localization, we develop an exact (meaning no added conservatism) and optimal (smallest growth in the number of variables) closed-form definition for the convex hull of Convex Constrained Generators (CCGs). This results in a more efficient method to represent the minimum volume convex set corresponding to the state estimation. Given that reductions methods are still lacking in the literature for CCGs, we employ an approximation using ray-shooting that is comparable in terms of accuracy with methods for Constrained Zonotopes as the ones implemented in CORA. Simulations illustrate the greater accuracy of CCGs with the proposed convex hull operation in comparison to Constrained Zonotopes.
|
|
17:40-18:00, Paper ThC06.6 | |
Set-Membership Estimator for Multi-Sensor Systems: A Collector-Based Approach |
|
He, Jiesi | Tsinghua University |
Xu, Feng | Tsinghua Univerisity |
Wang, Xueqian | Tsinghua University |
Wang, Ye | The University of Melbourne |
Keywords: Observers for linear systems, Time-invariant systems, Multi-agent systems
Abstract: This paper considers a distributed state estimation problem of a multi-sensor linear time-invariant system affected by bounded disturbances and measurement noise. We propose a zonotopic state estimation scheme, called collector, which generates a directed rooted tree from the underlying graph by designating a node to collect information. Based on this idea, multi-hop decomposition is implemented, and properties of multi-hop decomposition under this framework are discussed. Furthermore, this paper presents a solution for treating one node as a collector. In the end, a case study is used to illustrate the effectiveness of the proposed estimator.
|
|
ThC07 |
Room 312 |
Networked Systems |
Regular Session |
Chair: Stursberg, Olaf | University of Kassel |
Co-Chair: Mendoza Avila, Jesus | Universidad Nacional Autónoma De México |
|
16:00-16:20, Paper ThC07.1 | |
On Optimal Synchronization of Diffusively Coupled Heterogeneous Van Der Pol Oscillators |
|
Trummel, Tabea | University of Kassel |
Liu, Zonglin | University of Kassel |
Stursberg, Olaf | University of Kassel |
Keywords: Networked systems, Optimal control theory, Time-varying systems
Abstract: This paper proposes a novel method to achieve and preserve synchronization for a set of connected heterogeneous Van der Pol oscillators. Unlike the state-of-the-art synchronization methods, in which a large coupling gain is applied to couple any pair of connected oscillators, the proposed method first casts the whole synchronization process into two phases. The first one considers the period from the beginning to the first instant of synchronization, while the second phase covers the following time in which synchronization must be preserved. It is shown that a large coupling gain is adopted for the first phase, while the averaged coupling gain to preserve the synchronization in the second phase can be reduced significantly by using an offline optimized coupling law. Efficiency and performance of this method are confirmed by a set of numerical tests with different graphs and system dynamics.
|
|
16:20-16:40, Paper ThC07.2 | |
Proportional and Derivative Coupling: A Way to Achieve Synchronization for Coupled Oscillators |
|
Wei, Bin | Texas a & M University - Kingsville |
Keywords: Control of interconnected systems, Dynamics and control, Modelling complexity
Abstract: In order to achieve synchronization, the concept of proportional coupling and derivative coupling, as analogue to PD control theory, is proposed. The author analyzes from the coupled simple harmonic oscillators to Kuromoto model, and to the coupled Van der Pol oscillators. It is conjectured that only proportional coupling for two or multiple linear and nonlinear coupled oscillators is not sufficient most of the time to achieve synchronization, whereas derivative coupling is the dominant factor for two or multiple linear and nonlinear coupled oscillators to get synchroni | |