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63rd IEEE Conference on Decision and control, CDC 2024

作者： Grapentin, Aaron Hans, Christian A. Raisch, Jorg University of Kassel Automation and Sensorics in Networked Systems Group Germany Technische Universität Control Systems Group Berlin Germany Science of Intelligence Research Cluster of Excellence Berlin Germany

ISBN: (纸本)9798350316339

In this paper, a robust linear quadratic optimal control approach for accurate active power tracking of wind turbines is presented. For control synthesis, linear matrix inequalities are employed using an augmented wind turbine state model with uncertain parameters. The optimization problem for controller synthesis is derived from standard linear quadratic optimal control but extended to multiple operating points. The resulting controller ensures robust stability in different operating regions. In a case study, the novel approach is compared to existing controllers from literature. Simulations indicate that the controller improves power tracking accuracy while leading to similar mechanical wear as existing approaches. © 2024 IEEE.

关键词： Wind turbines

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Model Identification and control of Electromagnetic Actuation in Continuous Casting Process With Improved Quality

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 203-215页

作者： Isabela Birs Cristina Muresan Dana Copot Clara Ionescu Research Group of Dynamical Systems and Control Faculty of Engineering and ArchitectureGhent University and with EEDT Decision&ControlFlanders Make ConsortiumTech Lane Science Park 125 and 131B-9052 GhentBelgium.I.Birs the Automation Department Faculty of Automation and Applied InformaticsTechnical University of Cluj-NapocaRomania IEEE

This paper presents an original theoretical framework to model steel material properties in continuous casting line process. Specific properties arising from non-Newtonian dynamics are herein used to indicate the natural convergence of distributed parameter systems to fractional order transfer function models. Data driven identification from a real continuous casting line is used to identify model of the electromagnetic actuator device to control flow velocity of liquid steel. To ensure product specifications, a fractional order control is designed and validated on the system. A projection of the closed loop performance onto the quality assessment at end production line is also given in this paper.

关键词： Electromagnetic actuator fractional order control fractional order system model non-Newtonian material

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Predictive Linear Online Tracking for Unknown Targets 41

Predictive Linear Online Tracking for Unknown Targets

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41st International Conference on Machine Learning, ICML 2024

作者： Tsiamis, Anastasios Karapetyan, Aren Li, Yueshan Balta, Efe C. Lygeros, John Automatic Control Laboratory ETH Zürich Zürich Switzerland Institute for Dynamic Systems and Control ETH Zürich Zürich Switzerland Control and Automation Group Inspire AG Zürich Switzerland

In this paper, we study the problem of online tracking in linear control systems, where the objective is to follow a moving target. Unlike classical tracking control, the target is unknown, non-stationary, and its state is revealed sequentially, thus, fitting the framework of online non-stochastic control. We consider the case of quadratic costs and propose a new algorithm, called predictive linear online tracking (PLOT). The algorithm uses recursive least squares with exponential forgetting to learn a time-varying dynamic model of the target. The learned model is used in the optimal policy under the framework of receding horizon control. We show the dynamic regret of PLOT scales with O(√TVT), where VT is the total variation of the target dynamics and T is the time horizon. Unlike prior work, our theoretical results hold for non-stationary targets. We implement PLOT on a real quadrotor and provide open-source software, thus, showcasing one of the first successful applications of online control methods on real hardware. Copyright 2024 by the author(s)

关键词： Target tracking

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On the Regret of Recursive Methods for Discrete-Time Adaptive control with Matched Uncertainty 63

On the Regret of Recursive Methods for Discrete-Time Adaptiv...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Karapetyan, Aren Balta, Efe C. Tsiamis, Anastasios Iannelli, Andrea Lygeros, John Automatic Control Laboratory Zürich8092 Switzerland Control and Automation Group Inspire Ag Zürich8005 Switzerland Automatic Control Laboratory Switzerland University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart70569 Germany

ISBN: (纸本)9798350316339

Continuous-time adaptive controllers for systems with a matched uncertainty often comprise an online parameter estimator and a corresponding parameterized controller to cancel the uncertainty. However, such methods are often impossible to implement directly, as they depend on an unobserved estimation error. We consider the equivalent discrete-time setting with a causal information structure, and propose a novel, online proximal point method-based adaptive controller, that under a sufficient excitation (SE) condition is asymptotically stable and achieves finite regret, scaling only with the time required to fulfill the SE. We show the same also for the widely-used recursive least squares with exponential forgetting controller under a stronger persistence of excitation condition. © 2024 IEEE.

关键词： Discrete time control systems

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Safe Risk-Averse Bayesian Optimization for controller Tuning

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IEEE Robotics and automation Letters 2023年第12期8卷 8208-8215页

作者： Konig, Christopher Ozols, Miks Makarova, Anastasia Balta, Efe C. Krause, Andreas Rupenyan, Alisa Inspire Ag Control and Automation Group Zurich8005 Switzerland Eth Zurich Automatic Control Laboratory Zurich8092 Switzerland Eth Zurich Learning & Adaptive Systems Group Zurich8092 Switzerland Zhaw Zurich University of Applied Sciences Zhaw Centre for Artificial Intelligence Winterthur8400 Switzerland

controller tuning and parameter optimization are crucial in system design to improve both the controller and underlying system performance. Bayesian optimization (BO) has been established as an efficient model-free method for controller tuning and adaptation. Standard methods, however, are not enough for high-precision systems to be robust with respect to unknown input-dependent noise and stable under safety constraints. In this work, we present a novel data-driven approach, RAGoOSe, for safe controller tuning in the presence of heteroscedastic noise, combining safe learning with risk-averse Bayesian optimization. We demonstrate the method for synthetic benchmark and compare its performance to established BO-based tuning methods. We further evaluate RaGoose performance on a real precision-motion system utilized in semiconductor industry applications and compare it to the built-in auto-tuning routine. © 2016 IEEE.

关键词： Benchmarking

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Event-Based Fractional Order MIMO control for Hemodynamic Stabilization during General Anesthesia

Event-Based Fractional Order MIMO Control for Hemodynamic St...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Birs, Isabela Muresan, Cristina Ghita, Mihaela Ghita, Maria Nascu, Ioana Ionescu, Clara Technical University of Cluj-Napoca Automation Department Romania Ghent University DySC Research Group on Dynamical Systems and Control Belgium

ISBN: (纸本)9798350337020

General anesthesia is used to induce a reversible loss of consciousness in a patient to ensure they are completely unaware and pain-free during a surgical procedure. This is achieved through the administration of a combination of drugs that depress the central nervous system and can include intravenous injections, inhaled gases, or a combination of both. During the anesthesia maintenance phase, the events in surgery are not continuous, but obey a profile similar to that endorsed by event-based control. The present study considers event-based control as a natural solution to the control challenge of general anesthesia. Two fractional order Proportional Integral (PI) controllers are tuned and implemented using a decentralized approach to control a part of general anesthesia based on hemodynamic variables. The results show that this approach can be successfully used to keep Cardiac Output and Mean Arterial Pressure stable, with a special focus on patient safety, through fast detection of surgical stimulus and robustness to inter/intra patient variability. © 2023 IEEE.

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Uncertainty and its Effect on Optimal Multidrug control of Hemodynamic Variables

Uncertainty and its Effect on Optimal Multidrug Control of H...

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2024 American control Conference, ACC 2024

作者： Popescu, Teodora Birs, Isabela R. Othman, Ghada Ben Yumuk, Erhan Mihai, Marcian Hegedus, Erwin Copot, Dana De Keyser, Robin Ionescu, Clara M. Muresan, Cristina I. Technical University of Cluj-Napoca Department of Automation Cluj-Napoca Romania Ghent University Research Group on Dynamical Systems and Control Department of Electromechanics Systems and Metal Engineering Tech Lane Science Park 125 Gent9052 Belgium Istanbul Technical University Department of Control and Automation Engineering Maslak Istanbul34469 Turkey

ISBN: (纸本)9798350382655

Computer aided control in biomedical applications is gaining more and more popularity due to numerous research studies that have proven the efficiency of automatic control over manual dosing, which is highly susceptible to human errors. Optimal drug dosing is best achieved using automatic control, which triggers important benefits in terms of both costs and patient side-effects. However, mathematical models for patients are highly susceptible to large modeling uncertainty. A predictive control algorithm is designed in this paper for optimal multidrug control of hemodynamic variables. Improved closed loop performance is obtained compared to similar control strategies, for ± 30% modeling uncertainty. The simulation results demonstrate that predictive control is a feasible solution for optimal drug dosing. An analysis of the closed loop performance for significant patient variability shows that controllers tuned using a nominal patient model often fail to achieve desired robustness. To limit the effect of modeling uncertainty, the prediction model should be updated using an online identification tool to extract patient features. © 2024 AACC.

关键词： Predictive control systems

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Structural Coverability for Intelligent automation systems 19

Structural Coverability for Intelligent Automation Systems

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19th IEEE International Conference on automation Science and Engineering, CASE 2023

作者： Eros, Endre Bengtsson, Kristofer Åkesson, Knut Chalmers University of Technology Automation Research Group Electrical Engineering Systems and Control Department Gothenburg Sweden Research and Technology Development Volvo Group Smart and Connected Operations Gothenburg Sweden

ISBN: (纸本)9798350320695

In order to be flexible and handle complex scenarios, intelligent automation systems might benefit from automated planning techniques which rely on specifications and models describing their behavior. However, due to the presence of message passing, latency, jitter, timeouts, failures, and error handling, the verification of such behavior models using formal methods is often unfeasible. Therefore, testing has emerged as an approach to evaluating the behavior of intelligent automation systems. This paper presents a way to analyze structural coverability of behavior models for intelligent automation systems, which is inspired by the modified condition/decision coverage (MC/DC) criterion. This is paired with a testing procedure that enables each test case to influence both the controller and the simulated environment by injecting some specific state. As a result, the proposed coverability criterion can effectively identify segments of the behavior model that have not been adequately tested and suggest additional test cases to improve coverability. An example use case is presented to demonstrate the effectiveness of this approach. © 2023 IEEE.

关键词： Message passing

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Indirect adaptive higher order sliding mode control for third order systems in parametric strict-feedback form 63

Indirect adaptive higher order sliding mode control for thir...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Watermann, Lars Andritsch, Benedikt Koch, Stefan Reichhartinger, Markus Horn, Martin Reger, Johann Technische Universität Ilmenau P.O. Box 100565 Control Engineering Group P.O.Box 100565 Ilmenau98684 Germany Institute of Automation and Control Graz University of Technology Graz Austria Institute of Automation and Control Graz University of Technology Christian Doppler Laboratory for Model-Based Control of Complex Test Bed Systems Graz Austria

ISBN: (纸本)9798350316339

In this contribution the design of an indirect adaptive third order sliding mode controller based on a backstepping-like procedure is presented. A recursively defined homogeneous control Lyapunov function is combined with the adaptive backstepping method via tuning functions to compensate for unmatched parametric uncertainties. A matched bounded disturbance is eliminated by discontinuous control. It is shown that the states of the regarded system in parametric strict-feedback form converge asymptotically to the equilibrium while the parameter estimation error is bounded. Further, it is guaranteed that all control and adaptation signals are bounded. The proposed design is demonstrated in a simulation of a system with unmatched parametric uncertainty and matched disturbance. © 2024 IEEE.

关键词： Sliding mode control

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System Class Extensions of the Modulating Function based State Reconstruction for the Advection-Diffusion-Reaction Equation

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IEEE Transactions on Automatic control 2025年

作者： Friedrich, Folke Fokken, Nils Noack, Matti Reger, Johann Institute for Automation and Systems Engineering Technische Universität Ilmenau Control Engineering Group Ilmenau98693 Germany

In this paper, the state estimation of distributed parameter systems (PDEs) using the Modulating Function Method is extended to systems of two or higher spatial dimensions with spatially varying coefficients and general boundary conditions. At the center of the PDE observer approach lies the construction and solvability analysis of systematically obtained kernel equations determining the modulating functions. Additionally, a method for the state estimation of a class of parabolic systems with time-varying and nonlinear parameters based on Volterra integral transformations is presented. Furthermore, a linearization based strategy to deal with nonlinear reaction terms is presented. The stability of the resulting iterative feedback algorithm is proven. Numerical simulations show the validity and robustness of the methodology in two simulated examples. © 1963-2012 IEEE.

关键词： Iterative methods

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