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Functional interval estimation for continuous-time linear systems with time-invariant uncertainties

AUTOMATICA 2025年 172卷

作者： Ma, Youdao Wang, Zhenhua Meslem, Nacim Raissi, Tarek Harbin Inst Technol Dept Control Sci & Engn Harbin 150001 Peoples R China Univ Grenoble Alpes CNRS GIPSA Lab INP F-38000 Grenoble France Conservatoire Natl Arts & Metiers CNAM F-75141 Paris France

This paper investigates functional interval estimation for continuous-time linear systems subject to both time-varying and time-invariant uncertainties. Two novel methods are proposed based on peak-to-peak functional observer design and interval analysis. First, we present a splitting-based method that splits the estimation error dynamics into two subsystems to handle the time-invariant disturbances and provide accurate estimation results. Then, to further enhance the estimation accuracy, we present an augmentation-based method that considers the time invariance in both functional observer design and reliable interval estimation. The relationship between a state-of-art method and the proposed methods are analysed theoretically. Finally, simulation results are provided to demonstrate the performances of the proposed methods. (c) 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： Functional interval estimation time invariance continuous-time linear systems Peak-to-peak performance index Interval analysis

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Model-free distributed optimal control for continuous-time linear systems

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IET CONTROL THEORY AND APPLICATIONS 2022年第16期16卷 1685-1695页

作者： Feng, Xinjun Zhao, Zhiyun East China Univ Sci & Technol Dept Automat Shanghai Peoples R China

This paper studies the distributed optimal consensus problem for a group of continuous-time linear systems in the scenario that the dynamics of linear systems are completely unknown. Both an optimal state feedback control law and an optimal output feedback control law are constructed by solving the Algebraic Riccati Equation (ARE) that contains no global information, which guarantees the consensus of linear systems and the global optimality. Adaptive Dynamic Programming (ADP) method is presented to solve the ARE, thus the control algorithms are not relying on the dynamics of linear systems any more. Finally, numerical simulation results are presented to demonstrate the efficiency of proposed approach.

关键词： model-free distributed optimal control Riccati equations ARE linear systems optimal state feedback control law ADP method adaptive dynamic programming method dynamic programming global optimality continuous time systems algebraic Riccati equation optimal output feedback control law state feedback optimal control distributed optimal consensus problem continuous-time linear systems

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Functional Interval Estimation for continuous-time linear systems 22

Functional Interval Estimation for Continuous-Time Linear Sy...

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22nd World Congress of the International Federation of Automatic Control (IFAC)

作者： Ma, Youdao Wang, Zhenhua Meslem, Nacim Raissi, Tarek Luo, Hao Harbin Inst Technol Sch Astronaut Harbin 150001 Peoples R China Univ Grenoble Alpes CNRS GIPSA lab F-38000 Grenoble France Conservatoire Natl Arts & Metiers CNAM F-75141 Paris France

ISBN: (纸本)9781713872344

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. Copyright (c) 2023 The Authors. This is an open access article under the CC BY-NC- ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Functional interval estimation continuous-time linear systems robust functional observer interval analysis

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Reliable Unknown Input Observer for continuous-time linear systems 11th

Reliable Unknown Input Observer for Continuous-Time Linear S...

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11th International-Federation-of-Automatic-Control (IFAC) Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

作者： Meslem, Nacim Hably, Ahmad Raissi, Tarek Wang, Zhenhua Univ Grenoble Alpes GIPSA Lab Grenoble INP CNRS F-38000 Grenoble France Conservatoire Natl Arts & Metiers 292 Rue St Martin F-75141 Paris France Harbin Inst Technol Dept Control Sci & Engn Harbin 150001 Peoples R China

This work proposes a set-valued extension of the classical unknown input observers for linear continuous-time systems without using set-by-step set-membership computations or imposing the positivity property of the dynamics of the estimation error. In fact, based on an explicit set-integration method of the estimation error, the framing and convergence properties of the proposed set-valued unknown input observer are demonstrated. Moreover, thanks to the proposed design approach, robust threshold on the residual can be established a priori. Simulation results are reported to highlight the effectiveness of the proposed state estimator in the presence of unknown inputs. Copyright (C) 2022 The Authors.

关键词： State estimation continuous-time linear systems unknown input observer interval observer set-membership estimation reachability analysis

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Functional Interval Estimation for continuous-time linear systems*

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IFAC-PapersOnLine 2023年第2期56卷 8482-8487页

作者： Youdao Ma Zhenhua Wang Nacim Meslem Tarek Raïssi Hao Luo School of Astronautics Harbin Institute of Technology Harbin 150001 P. R. China Univ. of Grenoble Alpes CNRSGIPSA-lab F-38000 Grenoble France Conservatoire National des Arts et Métiers(CNAM) Paris 75141 France

关键词： Functional interval estimation continuous-time linear systems robust functional observer interval analysis

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Reliable Unknown Input Observer for continuous-time linear systems

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IFAC-PapersOnLine 2022年第6期55卷 248-253页

作者： Nacim Meslem Ahmad Hably Tarek Raïssi Zhenhua Wang Univ. Grenoble Alpes CNRS Grenoble INP GIPSA-lab 38000 Grenoble France Conservatoire National des Arts et Métiers 292 Rue Saint-Martin 75141 Paris France Department of Control Science and Engineering Harbin Institute of Technology Harbin 150001 P. R. China

This work proposes a set-valued extension of the classical unknown input observers for linear continuous-time systems without using set-by-step set-membership computations or imposing the positivity property of the dynamics of the estimation error. In fact, based on an explicit set-integration method of the estimation error, the framing and convergence properties of the proposed set-valued unknown input observer are demonstrated. Moreover, thanks to the proposed design approach, robust threshold on the residual can be established a priori . Simulation results are reported to highlight the effectiveness of the proposed state estimator in the presence of unknown inputs.

关键词： State estimation continuous-time linear systems unknown input observer interval observer set-membership estimation reachability analysis

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Robust Static Output Feedback Stabilization of continuous-time linear systems via Enhanced LMI Conditions 21st

Robust Static Output Feedback Stabilization of Continuous-Ti...

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21st IFAC World Congress on Automatic Control - Meeting Societal Challenges

作者： Gritli, Hassene Zemouche, Ali Belghith, Safya Laleg-Kirati, Taous-Meriem Univ Carthage Higher Inst Informat & Commun Technol 1164 Borj Cedria Tunis Tunisia Univ Lorraine CRAN CNRS UMR 7039 F-4400 Cosnes Et Romain France Univ Tunis El Manar Lab Robot Informat & Complex Syst RISC Lab LR16ES Natl Engn Sch Tunis BP 37 Tunis 1002 Tunisia King Abdullah Univ Sci & Technol KAUST Math & Computat Sci & Engn Div Thuwal Saudi Arabia

This paper addresses the problem of Static Output Feedback (SOF) stabilization for continuous-time linear systems subject to norm-bounded parameter uncertainties. Usually this issue leads to the feasibility of a Bilinear Matrix Inequality (BMI), which is difficult to linearize to get non conservative linear matrix inequality (LMI) conditions. In this paper, by means of some technical lemmas, we transform the BMI into a new LMI with a line search over two scalar variables. The obtained LMI conditions are less conservative than those existing in the literature. Numerical evaluations are presented to show the superiority of the proposed method. Copyright (C) 2020 The Authors.

关键词： continuous-time linear systems Robust control Parametric uncertainty Static output feedback linear matrix inequality (LMI)

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Robust Static Output Feedback Stabilization of continuous-time linear systems via Enhanced LMI Conditions

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IFAC-PapersOnLine 2020年第2期53卷 4540-4545页

作者： Hassène Gritli Ali Zemouche Safya Belghith Taous-Meriem Laleg-Kirati Higher Institute of Information and Communication Technologies Université de Carthage 1164 Borj Cedria Tunis Tunisia University of Lorraine CRAN CNRS UMR 7039 54400 Cosnes et Romain France Laboratory of Robotics Informatics and Complex Systems (RISC Lab - LR16ES07) National Engineering School of Tunis Université de Tunis El Manar BP. 37 Le Belvédère 1002 Tunis Tunisia Mathematical and Computational Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Kingdom of Saudi Arabia

关键词： continuous-time linear systems Robust control Parametric uncertainty Static output feedback linear matrix inequality (LMI)

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A time-Delay Modeling Approach for Data-Driven Predictive Control of continuous-time systems

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 6408-6420页

作者： Liu, Juan Yang, Xindi Zhang, Hao Wang, Zhuping Yan, Huaicheng Tongji Univ Coll Elect & Informat Engn Shanghai 200092 Peoples R China Tongji Univ Dept Control Sci & Engn Shanghai 200092 Peoples R China Nanyang Technol Univ Continental NTU Corp Lab Singapore 639798 Singapore Tongji Univ Coll Elect & Informat Engn Dept Control Sci & Engn Shanghai 201203 Peoples R China Tongji Univ Shanghai Inst Intelligent Sci & Technol Shanghai 201804 Peoples R China Natl Key Lab Autonomous Intelligent Unmanned Syst Shanghai 201210 Peoples R China Frontiers Sci Ctr Intelligent Autonomous Syst Minist Educ Shanghai 201210 Peoples R China East China Univ Sci & Technol Sch Informat Sci & Engn Key Lab Adv Control & Optimizat Chem Proc Minist Educ Shanghai 200237 Peoples R China

This paper aims to predict future optimal control inputs for unknown continuous-time linear systems. In contrast to most existing approaches that generate control input without observation loss, the proposed control scheme analyzes causality between observation and sequence feedback from the time-delay series model, allowing for the existence of observation loss. These time-delay series can be viewed as multiplayer games over a temporal scale, then a temporal game-theoretic approach ensures system stability and performance. By integrating the Bellman principle, a data-driven adaptive dynamic programming algorithm is proposed to avoid system knowledge. Furthermore, the designed parallel data-driven predictive algorithm reduces the computational complexity. Finally, the applicability and effectiveness of the methodology are demonstrated through numerical simulations and practical experiments.

关键词： Predictive control Prediction algorithms Heuristic algorithms Dynamic programming Optimization Optimal control Predictive models Data-driven time-delay modeling continuous-time linear systems temporal game predictive control

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Orthogonal Polynomial Bases for Data-Driven Analysis and Control of continuous-time systems

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2024年第7期69卷 4307-4319页

作者： Rapisarda, P. van Waarde, Henk J. Camlibel, M. K. Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England Univ Groningen Bernoulli Inst Math Comp Sci & Artificial Intelli NL-9747 AG Groningen Netherlands

We use polynomial approximation theory to perform data-driven analysis and control of linear, continuous-time invariant systems. We transform the continuous-time input trajectories and state trajectories into discrete sequences consisting of the coefficients of their orthogonal polynomial bases representations. We show that the dynamics of the transformed input signals and state signals and those of the original continuous-time trajectories are described by the same system matrices. We investigate informativity, quadratic stabilization, and H-2-performance problems for continuous-time systems. We deal with the case in which machine-precision accuracy in the representation of continuous-time signals can be achieved from the data using a finite number of basis elements, and the case in which the approximation error is nonnegligible.

关键词： Trajectory Approximation error Chebyshev approximation System dynamics Standards Transforms Controllability H-2-performance continuous-time linear systems data-driven control informativity polynomial orthogonal basis quadratic stabilization

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