Keywords: Artificial Intelligence, Robotics
Abstract: The next generation of robots will soon get out of the secure and predictable environment of factories and will face the complexity and unpredictability of our daily environments. To avoid that robots fail lamely at the task they are programmed to do, robots will need to adapt on the go. I will present techniques from machine learning to allow robots to learn strategies to enable them to react rapidly and efficiently to changes in the environment. Learning the set of feasible solutions will be preferred over learning optimal controllers. I will review methods we have developed to allow instantaneous reactions to perturbation, leveraging on the multiplicity of feasible solutions. I will present applications of these methods for compliant control during human-robot collaborative tasks and for performing fast motion, such as catching flying objects.

Keywords: Power Electronics and Drives, Dissipativity and Passivity, Lyapunov Stability Methods
Abstract: This paper presents voltage regulation and maximum power point tracking (MPPT) control schemes for a class of DC-microgrids. The DC-microgrid under consideration consists of a photovoltaic (PV) panel, battery, along with constant resistance and constant power loads. In this study, a dynamic model of the DC-microgrid system is derived and described by a multi-input and multi-output nonlinear system with non-affine inputs. Based on the nonlinear model thus built, we design nonlinear controllers that globally regulate voltages to prescribe set points and maximize the power output from PV by virtue of the passive system theory for non-affine systems and Lyapunov stability. The effectiveness of the proposed control schemes is validated by simulations.

Keywords: Production and Manufacturing Industry, Process Industry, Data-Based Modelling
Abstract: In order to achieve ambitious climate goals also the accountability of the energy-intensive process industry to meet these goals has to be increased. Recently, the application of optimization methods gained attractiveness to overcome burdens and challenges towards the transition to more sustainable systems. Furthermore, the conventional commitment of energy supply units in energy-intensive industries is challenged due to frame conditions such as rising share of renewable generation and volatile supply, fluctuating energy prices, limited transmission capacities and attempts at digitalization in industry. One crucial parameter to overcome new burdens is enhancing flexibility. Thus, promising measures are the alignment of the operation of energy supply units. From the modeling perspective, a decisive factor here is to enable a tight and compact, accurate modeling of the operation of highly flexible energy systems in order to realize short optimization durations with feasible operation points. To meet requirements regarding the accuracy, a modeling approach considering varying part-load efficiencies and non-linear operation effects of industrial energy supply and conversion units was developed. In this contribution, a specific focus is laid on combined cycle units such as gas turbines with heat recovery steam generators and steam turbines. The realization of short optimization durations is achieved by the formulation of a tight and compact mixed-integer linear programs which is established for optimization applications due to increasing solver speed and ongoing improvement of solution algorithms. The addressed overarching goal of this work is to enable a suitable formulation of realistic energy supply unit behavior to meet current challenges of optimal operation of industrial energy systems under changing frame conditions.

Keywords: Production, Manufacturing and Process Industry, Data-Based Methods and Machine Learning, Nonlinear Control
Abstract: Cement production is an energy intensive process, on the other hand the product quality directly influences the economic benefit. In this work a nonlinear model predictive control is designed to achieve an optimal compromise between energy consumption, production volume, and product quality. Based on measurements from a 100 t/h rotary cement kiln a non-linear autoregressive NARMAX-model is identified, and cross validation of this model shows good accuracy for control design. A prediction of the most influential disturbance (quality of the feed material) is utilized, product quality can be defined as a set-point, and the optimization criterion is defined using time-varying performance weights. This design achieves good transient response while still guaranteeing that the desired production volume is met. Validation results of the model with measured data and simulation results for the closed-loop operation demonstrate the functionality of the proposed methodology.

Keywords: Data-Based Methods and Machine Learning, Mathematical Modelling and Simulation, Energy and Power Systems
Abstract: A data-driven modeling approach for a pilot scale Packed-Bed Regenerator is examined and insights are generalized. Training data is generated with a one dimensional physical simulation model, which covers a wide variety of operation conditions including full load and partial load behavior. The NARX Recurrent Neural Network architecture is used to create a model that is able to describe the complex behavior of the regenerator. A grey box modeling approach is proposed that utilizes feedback state variables and incorporates knowledge about the internal behavior of the device. Using this approach, the behaviour of the Packed-Bed Regenerator can be described accurately with multi-step ahead predictions. This work presents a first step towards data-driven modeling of dynamic processes in industrial applications. In addition to the presentation of important modeling key points for the proposed grey box model, important steps regarding data preprocessing are identified and insights in the applicability of different Neural Network architectures are discussed.

Keywords: Motion and Vibration Control, Precision Systems, Nonlinear Control
Abstract: The high tech industry which requires fast stable motion with nanometer precision continues to mainly use PID which is limited by fundamental linear control limitations. Floor vibrations as disturbance significantly affect performance and their rejection is particularly affected by these limitations. Reset control has provided a promising alternative to surpass these, while simultaneously allowing the use of industry standard loop-shaping during design. However, the reset action introduced higher order harmonics can induce unwanted dynamics and negatively influence performance. This paper investigates two reset control strategies namely (1) band-pass phase lag reduction and (2) phase compensation to reduce the negative effects of higher order harmonics. The strategies are tested on a precision positioning stage for vibration rejection and the results show that phase compensation provides better performance compared to other tested strategies.

Keywords: Motion and Vibration Control, Elektromagnetic Actuators and Electric Machines, System Design and Integration
Abstract: An active dynamic vibration absorber is introduced to a cyropump system achieving ultra-high vacuum and extremely low temperature environments for fine observation and high-accuracy measurement. In a cryopump, a so-called displacer moves reciprocally for alternative adiabatic expansion and exhaust of helium gas. Such a motion induces vibration in the vacuum chamber on which the pump is fixed. It may negatively affect observation and measurement performed in the chamber. To remove this vibration effectively, an active dynamic vibration absorber is designed, fabricated and installed in the system. Both empirical and model-based approaches are applied in reducing vibration at multiple specified frequencies. Finally, the vibration is almost eliminated at five specified frequencies.

Keywords: Precision Systems, Motion and Vibration Control, System Design and Integration
Abstract: This paper proposes a sample-tracking vibration isolator based on hybrid reluctance actuators to bring a vibration sensitive instrument toward inline metrology. The hybrid reluctance actuators vertically move the platform to mount the instrument and maintain its position with respect to the target sample, rejecting floor vibrations. For compensating cross-talk motions due to manufacturing and assembly tolerances, the actuator forces are balanced, demonstrating a reduction by a factor of about 10 for frequencies below 70 Hz. In order to regulate the moving platform motion, a feedback controller is designed achieving a closed-loop bandwidth of 260 Hz. Experiments reveal that the proposed vibration isolator reduces the vibrations (RMS value) from 37.5 nm to 1.6 nm and consequently realizes nanometer positioning resolution in a vibrational environment. These experiments successfully demonstrate the effectiveness of the proposed vibration isolator and the capability of the hybrid reluctance actuators to handle floor vibrations.

Keywords: Smart Actuators, Micro- and Nano-sensors, Motion and Vibration Control
Abstract: Piezo actuators are widely used in high-precision equipment where accurate nanometer positioning is required. Piezo material, like PZT, show significant hysteretic behaviour, typically needing position feedback control or solutions like charge amplification to minimize hysteresis effects. Other materials like LiNbO₃ show linear behaviour themselves. Both, however, have an inherent high stiffness and lightly damped mechanical resonances leading to unwanted vibration. This paper investigates the use of self sensing in piezo's, using current and voltage in the electrical domain, for active damping purposes. In particular, the combination with charge control is shown, and a hysteresis cancellation technique is proposed.

Keywords: Motion and Vibration Control, Optomechatronic Systems
Abstract: Abstract: Mechanical vibrations resulting from wind, ground vibrations and actuator imperfections lower the performance of optical telescope systems used for astronomical applications, as well as free-space optical communication. This paper proposes a high-bandwidth tip-tilt compensation system for optical telescopes, in order to reduce the influence of these vibrations. A typical, high precision, motorized telescope system is used as a base for this evaluation. By utilization of a tip-tilt sensor, the resulting tip-tilt errors are measured and analyzed in the frequency domain. A fast steering mirror integrated into the optical path allows to compensate for the measured tip-tilt errors. The performance of the fast steering mirror based system is compared to the original, uncompensated system, as well as to a compensation loop, which uses the telescope mount to counteract measured errors. Experiments demonstrate a significant reduction of the tip-tilt errors due to vibrations by a factor of 5 (altitude axis) and by a factor of 4.6 (azimuth axis) utilizing a compensation bandwidth of up to 810 Hz.

Keywords: Mathematical Modelling and Simulation, Motion and Vibration Control, Smart Structures
Abstract: This paper investigates the feasibility of the linear parameter-varying (LPV) framework for modelling the dynamic behaviour of ultra-lightweight convertible structures based on the elastic kinetic motion mechanism with a focus on civil and structural engineering applications. Model building is carried out for the example of a Fin Ray structure. In a first step local linear time-invariant (LTI) models are derived from a finite element model of the structure for different transformation states. On the basis of this collection of local LTI models, a grid-based LPV model is established. The derived LPV model is validated in simulation by comparison with data from a finite element model.

Keywords: Observer and Filter Design
Abstract: This paper proposes a sliding mode differentiator for estimating the first-order derivatives of noisy signals. The proposed differentiator can be seen as a version of Slotine et al.'s sliding mode observer extended with additional non-Lipschitzness. It behaves exactly as a first-order low-pass filter in the sliding mode and is globally convergent. Its discrete-time implementation is based on the implicit (backward) Euler discretization, which does not result in chattering. The differentiator is validated through some numerical examples.

Keywords: Robust and Adaptive Control
Abstract: Discrete time sliding mode control (DSMC) strategies are well known to ensure good robustness of the system with respect to perturbations. However, since such algorithms specify dynamics of the plant on a step-by-step basis, their performance is deteriorated by the residual effect of past disturbance on the system state. To counteract this effect, in our paper we propose a new approach using a reference model of the plant. In this approach, a discrete time reaching law is first used to specify dynamics of the disturbance-free model. Then, a secondary control signal is obtained with the aim of driving the state of the actual plant alongside the desired trajectory provided by its model. As a result, only the single most recent disturbance term has an effect of the system state, which effectively enhances its sliding mode performance.

Keywords: Robust and Adaptive Estimation, Numerical Modelling Methods and Computational Aspects, Biological and Biomedical Systems
Abstract: The aim of this study was to design a step-by-step numerical differentiator for a class of discretized version of a n-th chain-of-integrator system based on the application of the implicit discretization of the super-twisting algorithm (STA). The high-order differentiator reconstructed the non-measurable states of an input-output linearizable systems. The gains of the observer were calculated based on the application of a class of generalized functions. The convergence analysis showed that all the states in the linearized system achieved an invariant set with a predefined size. The existence of this invariant set depends on the uniqueness of the solution for the generalized function. A simple interpretation of a possible exact reconstruction of the non-measurable states of the implicit discretized form. The application of the implicit discretized STA served to design a class of observer for the microalgae culture system.

Keywords: Robust and Adaptive Control, Control of Networked Systems
Abstract: In this paper, a sliding mode based control concept for networked control systems in the presence of variable time delays and external perturbations is proposed. The control concept consists of a buffering mechanism and a discrete time integral sliding mode based control law. This setting offers the possibility to use discrete-time sliding mode control techniques designed for relative degree one systems. As a consequence, networked control algorithms can be developed based on recent results from this active field of research. Using a discretized version of the super twisting algorithm, which is obtained by the so-called matching approach, increases the accuracy due to the absence of discretization chattering. The effectiveness of the proposed control strategy is demonstrated by means of laboratory experiments.

Keywords: Pneumatic and Hydraulic Systems, Control of Sampled-Data Systems, Robust and Adaptive Control
Abstract: Leak detection for electric vehicles experiences a rapidly increasing interest on the automotive after-sales market. As the contact of the battery cells with water is a high risk of damaging the battery its housing needs to be tested for tightness accurately. This paper shows the model-based design of a robust control concept employed for pressure control using a high-dynamic piezo valve. By keeping the pressure inside the housing at a constant vacuum the measured mass flow reveals the actual tightness of the battery pack. The robust control concept is designed using sliding mode concepts, i.e. a second-order super twisting algorithm. A new sophisticated discretization method is presented and compared to a standard explicit Euler time-discretization within experimental results. It shows that for higher sampling times the new discretization method shows superior performance in terms of control output chattering. This ensures good control quality as well as an increased actuator lifetime when being compared to standard methods.

Keywords: Output Regulation and Disturbance Rejection, Robust and Adaptive Control, Robust and Adaptive Estimation
Abstract: This paper proposes an extremum-seeking regulator design based on a Lie bracket averaging technique for time-varying nonlinear systems in the presence of unknown time-varying disturbance dynamics. The approach adopts a post-processing output regulation method for the regulation of nonlinear systems to the unknown minimum of a measured objective function. The stability analysis demonstrates that one can achieve practical output regulation of the unknown optimum equilibrium. A simulation study demonstrates the ability of the proposed technique to solve very general output regulation problems in the absence of exact knowledge of the process dynamics, the disturbance dynamics or a corresponding internal model.

Keywords: Iterative and Repetitive Learning Control
Abstract: This paper presents an extremum-seeking approach for accurate setpoint control of motion systems with friction, performing a repetitive motion. The classical PID controller, often used in industry for frictional motion systems, suffers from severe performance limitations. In particular, friction-induced limit cycling (hunting) is observed when integral control is employed on systems with unknown Stribeck friction, thereby compromising stability. Moreover, even if stability is warranted, transient performance highly depends on the particular frictional characteristic, which is typically uncertain. To deal with such uncertainty and to warrant optimal setpoint performance for the actual frictional properties, we propose a PID-based learning controller that achieves improved transient performance. Hereto, we consider a PID-type controller with a time-varying integral controller gain, which is adaptively obtained by employing a sampled-data extremum-seeking approach, resembling iterative learning control. The proposed approach does not require any knowledge on the friction characteristic. The working principle is illustrated by means of a representative simulation example.

Keywords: Stochastic Control, Robust and Adaptive Control, Control of Networked Systems
Abstract: We investigate stochastic averaging theory for time-varying nonlinear systems and its applications to convergence analysis of a distributed source seeking algorithm with time-varying topology. First, we present continuous-time stochastic averaging theorems for time-varying nonlinear systems with stochastic perturbations. Based on the method of stochastic extremum seeking, we propose a distributed stochastic source seeking algorithm with switching topology. We navigate multiple vehicles to seek the source of an unknown signal field, using the measurements of the signal field at their own positions and relative positions to their neighbors. Then, we apply our extended stochastic averaging theory to prove the local exponential convergence, both almost surely and in probability, to a small neighborhood near the source. Finally, a numerical example is included to illustrate the effectiveness of the algorithm.

Keywords: Robust and Adaptive Control, Model-Predictive and Optimal Control, Process Industry
Abstract: We design a Newton-like phasor-based Extremum Seeking Controller aimed at multi-variable nonlinear control systems. We first augment the derivative estimator underlying the phasor approach to capture the Hessian of the plant index. Then we use these estimates to steer the system along a Newton-like direction. We assess the closed-loop stability of the proposed scheme and demonstrate its effectiveness in a data center cooling scenario.

Keywords: Nonlinear Control, Hydraulic and Pneumatic Actuators, Automotive Systems
Abstract: Axial piston motors are core components in many hydro-mechanical systems as e.g. the powertrain of wheel loader vehicles. The optimal performance of the motor as well as the powertrain requires a fast and exact control of the motor's swivel angle according to the a-priori unknown reference signal which is e.g. generated by the driver with a joystick or gas pedal operation. Therefore, it is essential that the swivel angle controller fully exploits the possible dynamics and the constrained resources of the nonlinear swivel angle adjustment system. In this work, a novel flatness-based feedforward control strategy for the swivel angle is presented, which is capable of considering the relevant state and input constraints in real-time, i.e. only by means of the currently available information and without relying on an online optimization. The proposed swivel angle controller is finally demonstrated and discussed with the results of both a simulation study and measurement data from a wheel loader vehicle.

Keywords: Mathematical Modelling and Simulation, Elektromagnetic Actuators and Electric Machines, Nonlinear Control
Abstract: Flatness-based feed-forward control of solenoid actuators is considered. For precise motion planning and accurate steering of conventional solenoids, eddy currents cannot be neglected. The system of ordinary differential equations including eddy currents, that describes the nonlinear dynamics of such actuators, is not differentially flat. Thus, a distributed parameter approach based on a diffusion equation is considered, that enables the parametrization of the eddy current by the armature position and its time derivatives. In order to design the feed-forward control, the distributed parameter model of the eddy current subsystem is combined with a typical nonlinear lumped parameter model for the electrical and mechanical subsystems of the solenoid. The control design and its application are illustrated by numerical and practical results for an industrial solenoid actuator.

Keywords: Motion and Vibration Control, Estimation and Filtering
Abstract: In this research, we have proposed a stroke-oriented controller design for head positioning control system of hard disk drives (HDDs). A dual-stage actuator composed of a voice coil motor and a piezo actuator is widely used in the head positioning system. The decoupling filter design which decouples the interaction of each the actuator is a representitive controller design for the dual-stage actuator. However, it is necessary for the feedback loop related to the piezo actuator to increase the gain in the low frequency range due to design constraints. It can lead to increase a required stroke of the piezo actuator. The proposed controller design can decrease the required stroke of the piezo actuator by utilizing the interaction of each the actuator. To confirm the effectiveness the proposed controller design method, a simulation was performed to compensate for external vibrations. As the results, it was confirmed that the required stroke of the piezo actuator can be reduced by about 65%, while the stability and positioning accuracy of the head positioning control system is almost same as the that of decoupling filter design.

Keywords: Motion and Vibration Control, Precision Systems, Optimal Control
Abstract: Piezo-stepper actuators consist of piezo elements that are able to displace a mover over an infinite stroke through walking while maintaining the high accuracy and high stiffness properties of the piezo elements. The aim of this paper is to mitigate repetitive disturbances, that are introduced by the walking behaviour, to improve the performance of piezo-stepper actuators. The key challenge is to address repeating disturbances in the position domain, which may be varying in the time domain. A new position-domain iterative learning control procedure is presented that computes a signal in the commutation angle domain that mitigates the repetitive disturbances. The results from this procedure are exploited to determine an optimal waveform for the working range of the actuator. A significant improvement in performance is achieved after applying this waveform to a piezo-stepper actuator.

Keywords: Precision Systems
Abstract: This paper presents a hysteresis compensating control scheme that uses two piezoelectric transducers with similar hysteretic behavior. The transducers are supplied with the same voltage and the measured displacement of one of them is used to operate the other one in "open-loop", thereby reducing the hysteresis for a triangular reference signal with a frequency of 1Hz from 17.5% to 1.5%. In order to avoid a significant increase of the capacitive load of the piezo amplifier, two transducers of the same material but different sizes are used, which reduces the required current by 47% while maintaining the reduced hysteresis of the positioning system.

Keywords: Optimal Control, Elektromagnetic Actuators and Electric Machines, Nonlinear Control
Abstract: Aim of this study is to derive an efficient method and problem formulation for optimal control of induction machines in variable speed drives, as used for example in electric vehicles. Induction machine dynamics are thus represented as a differential flat system and voltage source inverter losses are considered as an average value model. Based on the canonical form of the equivalent flat system, a nonlinear discrete finite horizon optimal control problem with a predefined torque and speed profile is introduced. If it is required to find a global solution, this problem can be efficiently solved by discrete dynamic programming or, when time is of essence, by means of sequential quadratic programming. The former is applied to a practical electric vehicle load cycle with limiting voltage constraints. The solution demonstrates how optimal control methods may be beneficial to drive design.

Keywords: First-Principles Modelling, Model-Predictive Control, Mechatronic Systems and Devices
Abstract: A control system for constrained control of a nonlinear multibody aircraft is described which exploits a combination of a scalar reference governor and a Linear Quadratic Integral (LQ-I) controller for maneuver load alleviation, trajectory control and shape control. A nonlinear multibody aircraft model for longitudinal flight is used to develop and validate the control system performance. The scalar reference governor is designed based on the linearized model and ensures that the imposed state and control constraints are satisfied. The mismatch between the linearized model used by the reference governor for prediction and the nonlinear dynamics of the multibody aircraft is accounted for in the reference governor design. The paper demonstrates the feasibility of the adopted control approach, including constraint enforcement, based on the nonlinear model simulations of pitching maneuvers.

Keywords: Aerospace Systems, Nonlinear Control, Mathematical Modelling and Simulation
Abstract: Translational relative motion of a spacecraft in a gravity field can be induced by orientation changes. As orientation changes can be effected by electrically driven momentum exchange devices, for instance, reaction wheels, such maneuvers do not require fuel or thrust and hence can be performed during propulsion system failures or when the onboard fuel is limited. In this paper, a multi-mode controller is developed to effect such maneuvers which switches between control gains and intermediate target trajectories to extend the closed-loop domain of attraction of a conventional LQR controller and to satisfy state and control constraints.

Keywords: Observer and Filter Design, Robotics
Abstract: This paper deals with sensors and actuators fault detection in multirotor unmanned aerial vehicles whose dynamics are modeled as nonlinear systems. The considered approach is based on the differential flatness property of flat systems that provide analytical redundancy where every control input and system state can be expressed as a function of the flat outputs. By comparing the real measurements with their corresponding estimations deduced from the differentially flat equations, residual signals are computed and used for fault diagnosis. For multirotor UAV systems, only one set of flat outputs can be found. In this paper, it is shown that this unique set can be used to detect and isolate both sensors and actuators faults and failures. The effectiveness of this approach is illustrated by numerical simulations on Matlab/Simulink, and also a real experimental application on a hexarotor UAV.

Keywords: Robust and Adaptive Control, Observer and Filter Design, Robotics
Abstract: In this paper we provide an example of application of the design of a control law that makes use of an enhanced version of the so-called extended observer. The enhancement in question reposes on the extension of a classical Lemma due to Dayawansa to the case of nonlinear systems whose normal form includes time-varying (and measurable) gains. The presented example concerns a station-keeping problem of a quadrotor with unmeasurable pitch and roll angles.

Keywords: Nonlinear Control, Mathematical Modelling and Simulation
Abstract: This paper presents a model-based control approach for a tilted hexarotor with the purpose of controlling its mechanical impedance without requiring any force feedback. Based on the system model acquired with Lagrange formalism, an impedance based control approach is presented without requiring any force or torque feedback. The hexarotor is validated to behave as a damped mass-spring system in the simulation. The sensitivity of the proposed control is analyzed by evaluating the closed loop dynamics in terms of changes in the damping ratio and the eigenfrequency in dependence of the feedback delays, state estimation deviations and parameter uncertainties. The feedback delay, tilting angles and thrust coefficient are found to be the dominant factors, which affect the control performance.

Keywords: Mathematical Modelling and Simulation
Abstract: In this paper we present the comparison of two different approaches for designing the rotor tilt angles of a fully actuated aerial robot. A common approach is based on maximizing the forces and torques the robot can generate. To determine the tilt angles, simple knowledge of the maximum required wrench is necessary. Another approach focuses on following an a priori defined trajectory with minimum energy consumption, taking advantage of the nonlinear power-thrust characteristic of a real propeller. For this purpose, complex knowledge of the complete trajectory is necessary, especially for rotors with fixed orientation. Both approaches are systematically analyzed and compared with regard to energy saving potential of the energy based approach, depending on the chosen wrench trajectory. The energy based approach can be powerful for robots with in-flight adjustable rotors.

Keywords: Micro-/Nanosystems, Production, Manufacturing and Process Industry, Elektromagnetic Actuators and Electric Machines
Abstract: Printed electronics offer great potential for new applications such as Internet of Things devices and wearables. A methodology for integration of design and process assessment based on a stepwise transfer of the circuit to be printed from printed circuit board test vehicles to the final printed substrate is introduced. A multi-layer vector ink-jet printing process with three functional inks is presented using the example of the fabrication of a demonstrator circuit. This fabrication is realized using a newly set up printing system as enabling technology: Integration of a piezo print head into the path planning of the printing system and its control as virtual stepper axis enable highly precise vector printing yielding printed functional elements with low tolerances. Finally, process improvements for assembly of surface mounted devices on printed foil substrates are outlined.

Keywords: Optimal Control, Data-Based Methods and Machine Learning, Motion and Vibration Control
Abstract: Frequency Response Functions (FRFs) are essential for motion control design of complex mechatronic systems. The aim of this paper is to develop Optimal Experiment Design (OED) approaches for accurate identification of FRF models, with the particular focus on Multiple Input Multiple Output (MIMO) systems in closed-loop. The resulting optimization problem is shown to be highly challenging, especially for complex systems. A practical and feasible numerical approach based on a convex relaxation is developed. Experimental results on a next-generation wafer stage confirm that the quality of FRF measurements can be improved significantly using the proposed techniques.

Keywords: Production, Manufacturing and Process Industry, Motion and Vibration Control, Adaptive and Robust Control
Abstract: A novel continuously working force regulation algorithm aimed for the pick-and-place-units in a thermo-compression bonding application is proposed. The system setup considered consists of two co-linearly mounted axes. The larger of these axes is responsible for an accurate positioning. The controller of the smaller axis, which is mounted on the slide of the larger one, is designed as a nonlinear, adaptive impedance controller. The particular parameterization of this control structure has several advantages: It allows for small deflections of the second axis in non-contact case, small impact forces during touch-down and an accurate tracking of a desired force in contact case. Finally, it allows for a precise gap control in the case of a sudden collapse of the counteracting force which may occur in the application under consideration. The functionality of the proposed algorithm is shown on the basis of experimental studies.

Keywords: Robotic Manipulators, Production, Manufacturing and Process Industry
Abstract: This paper presents a design and implementation of a wafer transfer robotic system for a Foundry Equipment Innovation Competition. In this system, a 4-DOF robotic arm was designed and constructed for wafer transfer between a cassette and processing chambers. The purpose of this competition was to promote intelligent automation for wafer fabrication, in which multiple wafers and chambers need to be handled simultaneously. A scheduling algorithm is proposed for efficient task execution of wafer to process recipes assigned during the competition. The task also features to integrate defect detection and endpoint determination of wafer processing. The robot was required to receive the processing data from the mission platform to determine the endpoint of wafer processing in a chamber and complete the recipe automatically. The online inspection algorithm detects wafer defects during the task execution and report to the task planner. The state of each wafer and chamber are taken into consideration for scheduling in order to complete the wafer fabrication in an efficient and flexible manner. The developed robotic system spent 9 minutes to complete the assigned mission of transferring 6 wafers among multiple chambers and 2 cassettes and achieved 93.4% defect-detection rate in the competition.