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Adaptive Event-Triggered L 2-L? Control of Semi-Markov Jump distributed parameter systems

APPLIED MATHEMATICS AND COMPUTATION 2023年 439卷

作者： Mei, Yu Wang, Guanqi Shen, Hao Anhui Univ Technol AnHui Prov Key Lab Special Heavy Load Robot Maanshan 243032 Peoples R China Anhui Univ Technol Sch Elect & Informat Engn Maanshan 243032 Peoples R China

This paper focuses on the problem of adaptive event-triggered pound 2 - pound infinity control for dis-tributed parameter systems with semi-Markov jump parameters. An event-triggered trans-mission scheme, whose threshold function can be adaptively adjusted, is established to decrease the frequency of data transmission. Simultaneously, the utilization of limited net-work bandwidth resources is also improved due to plenty of "unnecessary" packets being discarded before accessing networks. Furthermore, the jumping of stochastic parameters in networks can be described by a semi-Markov jump model, in which the sojourn-time is considered subject to the Weibull distribution instead of the exponential distribution. Based on the aforesaid discussions, a mode-dependent controller is designed under an adaptive event-triggered scheme. Whereafter, some criteria are constructed based on the Lyapunov stability theory to guarantee stochastic stability and a prescribed pound 2 - pound infinity per-formance of the system. Ultimately, two simulation examples are provided to verify the feasibility of the proposed design approach.(c) 2022 Elsevier Inc. All rights reserved.

关键词： Semi-Markov jump systems distributed parameter systems Adaptive event -triggered scheme Stochastic stability

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Adaptive fault estimation and accommodation for distributed parameter systems with coupled parabolic partial differential equations

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JOURNAL OF CONTROL AND DECISION 2024年

作者： Ferdowsi, Farzin Cai, Jia Jagannathan, Sarangapani Northern Illinois Univ Elect Engn Dept 90 Garden Rd De Kalb IL 60115 USA Microsoft Corp Redmond WA USA Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO USA

This paper presents a novel model-based approach for fault detection, estimation and accommodation in linear distributed parameter systems (DPS) governed by parabolic partial differential equations (PDEs), prone to sensor and actuator faults. Unlike traditional methods, our approach utilises a filter-based observer directly employing the PDE representation and relies solely on boundary measurements, eliminating the need for extensive sensor arrays. By generating fault detection residuals from a comparison of measured and observer outputs, our method offers efficient fault detection. Innovative parameter update laws facilitate accurate estimation of fault parameters, enabling precise adjustment of the nominal controller to mitigate fault effects. Rigorous Lyapunov analysis ensures the robustness of our approach. Additionally, we derive a formula for estimating time-to-accommodation (TTA), providing valuable insights into fault resolution timelines. Simulations on a linearised diffusion process validate the effectiveness of our scheme, highlighting its superiority over existing approaches.

关键词： Fault detection fault-tolerant control adaptive control adaptive estimation distributed parameter systems partial differential equations

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Optimised data-driven terminal iterative learning control based on neural network for distributed parameter systems

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INTERNATIONAL JOURNAL OF AUTOMATION AND CONTROL 2021年第4-5期15卷 463-481页

作者： Dai, Xisheng Liu, Lanlan Deng, Zhenping Guangxi Univ Sci & Technol Sch Elect & Informat Engn Liuzhou 545006 Peoples R China Chongqing Jiaotong Univ Sch Informat Sci & Engn Chongqing 400074 Peoples R China Chongqing Keyuan Energy Technol Dev Ltd Chongqing 401147 Peoples R China

In this paper, a data-driven iterative learning control with neural network-based optimisation method for distributed parameter systems is presented to solve a class of problems caused by the imprecise mathematical model. The forward difference format is used to establish a linear relationship between input and output data, which is the only information available. However, this also leads to an unknown parameter matrix of the system. To overcome this problem, the radial basis function neural network is used to form a mapping relation from the desired output to the desired input, and the iterative learning algorithm of neural network weight is obtained by optimising the system performance indexes. Then, a detailed theoretical analysis based on composite energy function is given. Moreover, unlike traditional iterative learning control task tracking the whole trajectory, tracking time terminal is taken into account in this paper. Finally, simulation results show the feasibility of the theory.

关键词： data-driven control iterative learning control ILC distributed parameter systems DPSs neural network convergence

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Saturated Output Regulation of distributed parameter systems with Collocated Actuators and Sensors ⋆

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IFAC-PapersOnLine 2023年第2期56卷 8940-8945页

作者： Thavamani Govindaraj Lassi Paunonen Jukka-Pekka Humaloja Faculty of Information Technology and Communication Sciences Tampere University P.O.Box 692 33101 Tampere Finland University of Alberta 9211-116 St Edmonton AB T6G 1H9 Canada

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.

关键词： distributed parameter systems output regulation input saturation strongly stabilizable systems collocated input and output

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Event-Triggered Iterative Learning Control for First-Order MIMO Discrete Nonlinear Hyperbolic distributed parameter systems

Event-Triggered Iterative Learning Control for First-Order M...

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Data Driven Control and Learning systems (DDCLS)

作者： Xuhui Wang Xisheng Dai School of Automation Guangxi University of Science and Technology Liuzhou China Institute of Intelligent Systems and Control Guangxi University of Science and Technology Liuzhou China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

This paper studies the iterative learning control issue for a class of MIMO discrete nonlinear hyperbolic distributed parameter system with event-triggered strategy. The purpose of the event-triggered mechanism is to reduce the number of input updates in the iterative learning process. The event-triggered condition is about the error information of two previous adjacent iterative batches. Then an event-triggered iterative learning control algorithm is proposed. Rigorous mathematical analysis is shown, tracking error can converge to zero along the direction of iterative axis. Simulation results illustrates the effectiveness of the proposed event-triggered iterative learning control algorithm.

关键词： Learning systems Delay effects Simulation Mathematical analysis distributed databases Control systems distributed parameter systems

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On local exponential stability of equilibrium profiles of nonlinear distributed parameter systems 24

On local exponential stability of equilibrium profiles of no...

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24th International Symposium on Mathematical Theory of Networks and systems (MTNS)

作者： Hastir, A. Winkin, J. J. Dochain, D. Univ Namur Dept Math Rue Bruxelles 61 B-5000 Namur Belgium Univ Namur Namur Inst Complex Syst NaXys Rue Bruxelles 61 B-5000 Namur Belgium Catholic Univ Louvain Inst Informat & Commun Technol Elect & Appl Math Ave Georges Lemaitre 4-6 B-1348 Louvain La Neuve Belgium

Local exponential (exp.) stability of nonlinear distributed parameter, i.e. infinite dimensional state space, systems is considered. A weakened concept of Frechet differentiability ((Y, X)-Frechet differentiability) for nonlinear operators defined on Banach spaces is proposed, including the introduction of an alternative space (Y) in the analysis. This allows more freedom in the manipulation of norm inequalities leading to adapted Frechet differentiability conditions that are easier to check. Then, provided that the nonlinear semigroup generated by the nonlinear dynamics is Frechet differentiable in the new sense, appropriate local exp. stability of the equilibria for the nonlinear system is established. In particular, the nonlinear semigroup has to be Frechet differentiable on Y and (Y, X) Frechet differentiable in order to go back to the original state space X. This approach may be called "perturbation based" since exp. stability is also deduced from exp. stability of a linearized version of the nonlinear semigroup. Under adapted Frechet differentiability assumptions, the main result establishes that local exp. stability of an equilibrium for the nonlinear system is guaranteed as long as the exp. stability holds for the linearized semigroup. The same conclusion holds regarding instability. The theoretical results are illustrated on a convection-diffusion-reaction system. Copyright 2021 (C) The Authors.

关键词： distributed parameter systems Nonlinear systems Equilibrium Exponential stability

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Backstepping-based distributed abnormality localization for linear parabolic distributed parameter systems

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AUTOMATICA 2022年 135卷 109930-109930页

作者： Feng, Yun Wang, Yaonan Wang, Jun-Wei Li, Han-Xiong Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China Hunan Univ Natl Engn Lab Robot Visual Percept & Control Tech Changsha 410082 Hunan Peoples R China Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China City Univ Hong Kong Dept Adv Design & Syst Engn Kowloon Hong Kong Peoples R China

Abnormality localization for industrial processes described by distributed parameter systems (DPSs) is vital but seldom studied to the best of our knowledge. In this paper, a systematic framework is proposed to address this problem for a class of linear parabolic DPSs using a limited number of in-domain measurements plus one boundary measurement rather than the full-state measurement. The proposed methodology consists of an abnormality detection filter (ADF) and an abnormality localization filter (ALF) design based on the backstepping techniques and eigenspectrum. For the detection purpose, the residual is evaluated in a lumped manner;For the localization purpose, a distributed residual is first constructed and then evaluated in a distributed manner. Numerical simulations on a heat transfer rod are conducted to demonstrate the effectiveness of the proposed method. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： distributed parameter systems Fault detection Fault localization

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Frequency response-based decoupling tuning for feedforward compensation ADRC of distributed parameter systems

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CONTROL ENGINEERING PRACTICE 2022年第0期126卷

作者： Liu, Shaojie Zhang, Yu-Long Xue, Wenchao Shi, Gengjin Zhu, Min Li, Donghai Tsinghua Univ Dept Energy & Power Engn State Key Lab Power Syst Beijing 100084 Peoples R China Beijing Inst Technol Sch Math & Stat MIIT Key Lab Math Theory & Computat Informat Secu Beijing 100081 Peoples R China Chinese Acad Sci Acad Math & Syst Sci Key Lab Syst & Control Beijing 100190 Peoples R China Tsinghua Univ Key Lab Thermal Sci & Power Engn Dept Energy & Power Engn Minist Educ Beijing 100084 Peoples R China

A practical tuning method is proposed via frequency response or even cut-off frequency for active disturbance rejection control (ADRC) of distributed parameter systems (DPSs), whose models are hard to get but frequency characteristics are easy to measure. Moreover, a novel control structure, feedforward compensation ADRC (FC-ADRC), is presented to decouple the tuning of tracking and disturbance rejection (DR). The frequency response-based tuning method initializes the parameters and then iterates them to the optimal solution by following a simple rule. The basic idea of FC-ADRC is skillful. The closed-loop system is tuned to the desired dynamic via ADRC. Such a control system is a platform for a compensation block to be combined in cascade. ADRC only rejects disturbance while the feedforward compensation purely tracks. Simulation of six accepted irrational transfer functions (ITEs) shows the frequency response-based tuning for FC-ADRC performs better than compared control methods in robustness and performance of tracking and DR. The stability is proved based on the Nyquist criterion for DPSs. Two experiments verify the effectiveness of decoupling tuning and frequency response-based tuning. Therefore, frequency response-based tuning for FC-ADRC is not only a skillful and effective control structure but also a practical and compact method.

关键词： distributed parameter systems Two-degree-of-freedom control Active disturbance rejection control Frequency response-based tuning Feedforward compensation Nyquist criterion Monte Carlo method Control of water channel Control of magnetic levitation

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Spatial basis functions based fault localisation for linear parabolic distributed parameter systems

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IET CONTROL THEORY AND APPLICATIONS 2020年第20期14卷 3580-3588页

作者： Feng, Yun Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China Hunan Univ Natl Engn Lab Robot Visual Percept & Control Tech Changsha 410082 Hunan Peoples R China

Fault localisation for distributed parameter systems is as important as fault detection but is seldom discussed in the literature. The main reason is that an infinite number of sensors in the space are needed to construct a distributed residual signal, which is nearly impossible in practice. In this study, a fault detection and localisation filter which only uses a finite number of sensors is initiated based on an approximated ordinary differential equation model. Considering the limitations on computation resources for higher-order models in practice, a novel set of spatial basis functions is applied to the reduced-order fault detection and localisation filter design. Under certain conditions, the novel spatial basis functions obtain smaller state truncation error while the order is lower compared to the mostly used eigenfunctions of the spatial operator.

关键词： eigenvalues and eigenfunctions fault diagnosis reduced order systems distributed parameter systems differential equations linear parabolic distributed parameter systems fault localisation distributed residual signal approximated ordinary differential equation model higher-order models spatial basis functions reduced-order fault detection and localisation filter design spatial operator

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Off-policy integral reinforcement learning algorithm in dealing with nonzero sum game for nonlinear distributed parameter systems

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2020年第15期42卷 2919-2928页

作者： Ren, He Dai, Jing Zhang, Huaguang Zhang, Kun Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang Liaoning Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

Benefitting from the technology of integral reinforcement learning, the nonzero sum (NZS) game for distributed parameter systems is effectively solved in this paper when the information of system dynamics are unavailable. The Karhunen-Loeve decomposition (KLD) is employed to convert the partial differential equation (PDE) systems into high-order ordinary differential equation (ODE) systems. Moreover, the off-policy IRL technology is introduced to design the optimal strategies for the NZS game. To confirm that the presented algorithm will converge to the optimal value functions, the traditional adaptive dynamic programming (ADP) method is first discussed. Then, the equivalence between the traditional ADP method and the presented off-policy method is proved. For implementing the presented off-policy IRL method, actor and critic neural networks are utilized to approach the value functions and control strategies in the iteration process, individually. Finally, a numerical simulation is shown to illustrate the effectiveness of the proposal off-policy algorithm.

关键词： Integral reinforcement learning off-policy algorithm nonzero sum game distributed parameter systems adaptive dynamic programming

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