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International Conference on control, Mechatronics and Automation (ICCMA)

作者： Irfan Ahmad Fares M'zoughi Payam Aboutalebi Izaskun Garrido Aitor J. Garrido Automatic Control Group - ACG Department of Automatic Control and Systems Engineering Engineering School of Bilbao - EIB/BIE University of the Basque Country - UPV/EHU Bilbao Spain Department of Marine Technology Norwegian University of Science and Technology (NTNU) Moholt Trondheim Norway

Harnessing the power of wind and waves for renewable energy production has become vital in the quest for sustainable electricity generation. The fusion of Floating Offshore Wind Turbines (FOWTs) and Oscillating Water Columns (OWCs) has introduced a groundbreaking concept of hybrid offshore platforms, offering immense potential for energy absorption, reduced dynamic response, load mitigation, and improved cost efficiency. The primary goals of this study revolve around two key objectives: (i) the development of a regression-based modeling technique for the hybrid aero-hydro-elastic-servo-mooring coupled numerical system, and (ii) the implementation of a customized fuzzy-based control mechanism to ensure platform stability. To achieve these objectives, computational Machine Learning (ML) tools, specifically Artificial Neural Networks (ANNs), are utilized to replicate the behavior of the detailed numerical model of the FOWTs integrated with OWCs. Subsequently, a Fuzzy Logic control (FLC) scheme is employed to establish a structural controller that effectively mitigates unwanted vibrations. The experimental results confirm the potential of ANN-based modeling as a simpler yet effective alternative to complicated nonlinear NREL-5MW FOWT dynamical models. Furthermore, the use of the FLC system enhances platform stability in a variety of wind and wave conditions.

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Design of Robust Output Feedback controllers for Discrete-Time systems with Polynomial Uncertainties

Design of Robust Output Feedback Controllers for Discrete-Ti...

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International Conference on systems and control (ICSC)

作者： Robert Dehnert Sabine Lerch Michelle Rosik Andreas Rauh Bernd Tibken Institute of Automatic Control School of Electrical Information and Media Engineering University of Wuppertal Wuppertal Germany Group: Distributed Control in Interconnected Systems Carl von Ossietzky Universität Oldenburg Oldenburg Germany

This paper addresses the robust dynamic output feedback (DOF) problem for linear parameter-varying (LPV) discrete-time systems with polynomial dependence of uncertainties. For this purpose, the robust control problem is formulated via linear matrix inequalities (LMI) using Lyapunov's theory for a stability proof. Two relaxation methods are required to solve the robust LMI problem. The first is necessary to expand the Lyapunov stability condition to the structured linear control (SLC) problem for DOF controllers. The second type of relaxation is based on the theorem of Ehlich and Zeller and is required to include the polynomial dependence of uncertainties in the LMI design. These two relaxation methods yield an iterative LMI optimization approach. In this paper, we consider the specific example of a robust I-PD controller with a predefined decay rate that satisfies $H$ ∞ conditions for a polynomial parameter-dependent uncertain system.

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Decentralized Dynamic Disturbance Compensation control Strategy for Multiple Parallel Inverters in Microgrid 1

Decentralized Dynamic Disturbance Compensation Control Strat...

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1st IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2022

作者： Luo, Shanna Peng, Kaixiang Hu, Changbin Shi, Xiangyi Lu, Heng School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China School of Electrical and Control Engineering North China University of Technology Beijing China Tianjin Electric Power Design Institute Co. Ltd China Energy Engineering Group Tianjin China Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg47057 Germany

ISBN: (纸本)9798350398069

In order to enhance the anti-disturbance capability of voltage fluctuation during microgrid island operation, a decentralized dynamic disturbance compensation control strategy for multiple inverters in parallel based on robust residual generator is proposed. First, a parallel state space model of multiple inverters with line parameters under quasi-stationary line conditions is established. Secondly, for the double closed loop control structure of the inverter, a dynamic compensation controller Q(s) is designed from the perspective of disturbance cancellation, and its control signal is applied to the input terminal of the current loop to realize superposition with the original system current given signal. Then, a residual generator and a dynamic compensation controller Qi(s) are added to each parallel inverter to realize mutual influence among multiple inverters further decoupling. Finally, hardware-in-the-loop experiment on three inverters in parallel are designed on the RTDS platform to verify the effectiveness of the proposed strategy. © 2022 IEEE.

关键词： controllers

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Robust Sliding Mode control of a Quadrotor With Disturbance Rejection for Enhanced Stability and Performance

Robust Sliding Mode Control of a Quadrotor With Disturbance ...

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International Conference on Robotics and Artificial Intelligence (ICRAI)

作者： Hameed Ullah Owais Zarin Irfan Ahmad Sarfraz Ahmad Ansar Abbas Vincenzo Lippiello Department of Electrical Engineering and Information Technology University of Naples Federico II Naples Italy Department of Electrical Engineering Riphah International University Islamabad Pakistan ACG Department of Automatic Control and Systems Engineering Automatic Control Group School of Bilbao - EIB/BIE University of the Basque Country - UPV/EHU Bilbao Spain Department of Electrical Engineering CEME National University of Sciences and Technology (NUST) Islamabad Pakistan

ISBN: (数字)9798350355703

ISBN: (纸本)9798350355710

This research presents a comprehensive analysis of quadrotor stabilization and trajectory tracking control using Proportional-Integral-Derivative (PID) and Sliding Mode control (SMC) with integrated disturbance rejection. The nonlinear dynamics of the quadrotor are formulated using the Newton-Euler approach, accounting for six degrees of freedom. The PID controller is implemented as a baseline, while the SMC is designed for enhanced robustness to model uncertainties and external perturbations, with a disturbance observer for managing time-varying disturbances. A rigorous Lyapunov stability proof ensures global asymptotic stability of the SMC-controlled system. Extensive simulations evaluate both controllers in terms of tracking accuracy, control effort, and robustness to external disturbances. Results show that SMC outperforms PID in dis-turbance rejection, tracking accuracy, and robustness, making it ideal for UAV applications in complex environments.

关键词： Asymptotic stability Accuracy Uncertainty Trajectory tracking Robustness Stability analysis PD control Sliding mode control Quadrotors Lyapunov methods

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Comparative Analysis of Pharmacokinetic-Pharmacodynamic Models for Propofol and Remifentanil Using Model Predictive control

Comparative Analysis of Pharmacokinetic-Pharmacodynamic Mode...

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European control Conference (ECC)

作者： A. R. Ynineb H. Farbakhsh G. Ben Othman Y. Wahlquist I. R. Birs E. Yumuk C. I. Muresan R. De Keyser D. Copot C. M. Ionescu M. Neckebroek Department of Electromechanics Systems and Metal Engineering Research Group on Dynamical Systems and Control Ghent University Gent Belgium Department of Automatic Control Lund University Lund Department of Automation Technical University of Cluj-Napoca Cluj-Napoca Romania Department of Control and Automation Engineering Istanbul Technical University Maslak Istanbul Turkey Department of Anesthesia Ghent University Hospital Ghent Belgium

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This study aims to compare the effectiveness of different Pharmacokinetic-Pharmacodynamic (PK-PD) models for administering Propofol and Remifentanil, two critical agents in anesthesia. Initially, different PK models were introduced: one for Propofol based on the Schnider model and another for Remifentanil using the Minto model. Alternatively, both drugs were modeled using the Eleveld models. The PK-PD models were integrated into a closed-loop control system using model predictive control (MPC) with disturbances to control the Bispectral index (BIS) and the Richmond Agitation Sedation Scale (RASS). The methodology involved simulating the anesthetic agents in the open-source patient simulator (2 inputs, 2 outputs) with 12 patient datasets in a controlled environment to simulate the patient response variability, allowing for a detailed analysis of the model's performance in maintaining optimal drug concentrations. The primary focus was on the system's ability to adapt to surgical disturbances, a key challenge in anesthesia management, and whether a different modeling of drugs can have an impact on their effects. The results indicated significant differences in the performance of the two models configurations. The Eleveld model for Propofol showed less usage of drugs to maintain the desired BIS value. Concluding that this comparative analysis offers a valuable reference for selecting appropriate modeling approaches in the development of advanced control strategies in anesthesia.

关键词： Drugs Analytical models Adaptation models Surgery Europe Predictive models Anesthesia

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Consistent Event-Triggered Consensus on Complete Graphs

Consistent Event-Triggered Consensus on Complete Graphs

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IEEE Conference on Decision and control

作者： Duarte J. Antunes David Meister Toru Namerikawa Frank Allgöwer W.P.M.H. Heemels Dep. of Mechanical Eng. Eindhoven Control Systems Technology Group University of Technology the Netherlands Institute for Systems Theory and Automatic Control University of Stuttgart Germany School of Integrated Design Engineering Graduate School of Science and Technology Keio University Japan

This paper starts by considering an optimal control formulation of the consensus problem on complete graphs with a cost capturing disagreement and agents modeled by integrators. An optimal control policy for this problem is shown to be the well-known consensus algorithm by which each agent resets its state to the average of its and other agents' state values received at every time step. The framework is extended to the case where agents can only exchange information periodically, with a period larger than one. Then an event-triggered control strategy is proposed that results in a better cost than that of the optimal periodic one with the same average transmission rate, that is, it is consistent. According to this strategy, each agent distributedly transmits its state if the error between its current state and a common consensus estimate based on previously transmitted agents' data exceeds a threshold. Simulation results are presented to illustrate the proposed strategy.

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Correction to: Virtual flight deck crew assistance utilizing artificial intelligence methods to interpret NOTAMs: a user acceptance study (CEAS Aeronautical Journal, (2024), 15, 4, (1137-1144), 10.1007/s13272-024-00767-1)

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CEAS Aeronautical Journal 2025年第2期16卷 661-661页

作者： Dieter, Michelle Sprenger, Eric Pasnicu, Otilia Staudt, Josefine Ellenrieder, Nils Institute of Flight Systems and Automatic Control Technical University of Darmstadt Otto-Berndt-Str. 2 Darmstadt64287 Germany Work and Engineering Psychology Research Group Technical University of Darmstadt Alexanderstr. 10 Darmstadt64283 Germany

The article "Virtual fight deck crew assistance utilizing artifcial intelligence methods to interpret NOTAMs: a user acceptance study", written by Michelle Dieter, Eric Sprenger, Otilia Pasnicu, Josefne Staudt and Nils Ellenrieder, was originally published under exclusive license to Deutsches Zentrum für Luft- und Raumfahrt e.V. As a result of the subsequent decision to publish the article under the open access model, the article’s copyright notice was changed on 17 February 2025 to © The Author(s) 2025 and the article is now distributed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://***/licenses/by/4.0. Open access funding enabled and organized by Projekt DEAL. © The Author(s) 2025.

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System Level Synthesis for Affine control Policies: Model Based and Data-Driven Settings

arXiv

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arXiv 2025年

作者： Schüepp, Lukas De Pasquale, Giulia Dörfler, Florian Alonso, Carmen Amo Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zurich Physikstrasse 3 Zurich8092 Switzerland Computer Science Department of Stanford University Palo AltoCA United States Control Systems Group Department of Electrical Engineering TU Eindhoven Flux Groene Loper 19 Eindhoven5612AP Netherlands

There is an increasing need for effective control of systems with complex dynamics, particularly through data-driven approaches. System Level Synthesis (SLS) has emerged as a powerful framework that facilitates the control of large-scale systems while accounting for model uncertainties. SLS approaches are currently limited to linear systems and time-varying linear control policies, thus limiting the class of achievable control strategies. We introduce a novel closed-loop parameterization for time-varying affine control policies, extending the SLS framework to a broader class of systems and policies. We show that the closed-loop behavior under affine policies can be equivalently characterized using past system trajectories, enabling a fully data-driven formulation. This parameterization seamlessly integrates affine policies into optimal control problems, allowing for a closed-loop formulation of general Model Predictive control (MPC) problems. To the best of our knowledge, this is the first work to extend SLS to affine policies in both model-based and data-driven settings, enabling an equivalent formulation of MPC problems using closed-loop maps. We validate our approach through numerical experiments, demonstrating that our model-based and data-driven affine SLS formulations achieve performance on par with traditional model-based MPC. © 2025, CC BY.

关键词： Distributed parameter control systems

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Fuzzy Logic control of an Artificial Neural Network-Based Floating Offshore Wind Turbine Model Integrated with Four Oscillating Water Columns

SSRN

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SSRN 2022年

作者： Ahmad, Irfan M'zoughi, Fares Aboutalebi, Payam Garrido, Izaskun Garrido, Aitor J. Automatic Control Group—ACG Institute of Research and Development of Processes—IIDP Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao University of the Basque Country—UPV/EHU Po Rafael Moreno no3 Bilbao48013 Spain

The innovative hybrid offshore platform concept, which combines Floating Offshore Wind Turbines (FOWT) with Oscillating Water Columns (OWCs), has proven to be a promising solution to harvest clean energy. However, the dynamics of the tower and barge platform are extremely sensitive to wind speed and wave elevation, which causes substantial destabilization in extreme conditions, particularly to the tower-top-displacement and platform pitch angle. Therefore, the aim of this article is to focus on two main novel targets: (i) regressive modeling of the hybrid aero-hydro-elasto-servo-mooring coupled numerical system and (ii) an ad-hoc fuzzy-based control implementation for the stabilization of the platform. To analyze the performance of the hybrid FOWT, this article first employs computational Machine Learning (ML) techniques, i.e., Artificial Neural Networks (ANNs), to match the behavior of the detailed FOWT-OWCs numerical model. Then, FLC is developed and applied to establish a structural controller mitigating the undesired vibrations. Both modeling and control schemes are successfully implemented showing a superior performance when compared to the standard barge-based FOWT system. Experimental results demonstrate that the proposed ANN-based modeling is a promising alternative to other intricate non-linear NREL 5MW FOWT dynamical models. Meanwhile, the proposed FLC improves the platform's dynamic behavior with increasing its stability. © 2022, The Authors. All rights reserved.

关键词： Wind

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Parameter Filter-based Event-triggered Learning

arXiv

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arXiv 2022年

作者： Schlor, Sebastian Solowjow, Friedrich Trimpe, Sebastian University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart70550 Germany Institute for Data Science in Mechanical Engineering RWTH Aachen University Aachen52068 Germany Intelligent Control Systems Group Max Planck Institute for Intelligent Systems Stuttgart70569 Germany

Model-based algorithms are deeply rooted in modern control and systems theory. However, they usually come with a critical assumption – access to an accurate model of the system. In practice, models are far from perfect. Even precisely tuned estimates of unknown parameters will deteriorate over time. Therefore, it is essential to detect the change to avoid suboptimal or even dangerous behavior of a control system. We propose to combine statistical tests with dedicated parameter filters that track unknown system parameters from state data. These filters yield point estimates of the unknown parameters and, further, an inherent notion of uncertainty. When the point estimate leaves the confidence region, we trigger active learning experiments. We update models only after enforcing a sufficiently small uncertainty in the filter. Thus, models are only updated when necessary and statistically significant while ensuring guaranteed improvement, which we call event-triggered learning. We validate the proposed method in numerical simulations of a DC motor in combination with model predictive control. Copyright © 2022, The Authors. All rights reserved.

关键词： Stochastic systems

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