Data-driven optimal tracking control of switched linear systems

被引：10

作者：

Xu, Yichao ^{[1
,2
]}

Liu, Yang ^{[1
,2
,3
]}

Ruan, Qihua ^{[4
]}

Lou, Jungang ^{[5
]}

机构：

[1] Zhejiang Normal Univ, Key Lab Intelligent Educ Technol & Applicat Zheji, Jinhua 321004, Peoples R China

[2] Zhejiang Normal Univ, Sch Math Sci, Jinhua 321004, Peoples R China

[3] Linyi Univ, Sch Automat & Elect Engn, Linyi 276005, Peoples R China

[4] Putian Univ, Sch Math & Finance, Putian 351100, Peoples R China

[5] Huzhou Univ, Key Lab Smart Management & Applicat Modern Agr Re, Huzhou 313000, Peoples R China

来源：

NONLINEAR ANALYSIS-HYBRID SYSTEMS | 2023年 / 49卷

基金：

中国国家自然科学基金;

关键词：

Tracking control; Optimal control; Switched linear systems; Unknown dynamics; Data-driven; NONLINEAR-SYSTEMS; STABILITY; DESIGN;

D O I：

10.1016/j.nahs.2023.101355

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper addresses the optimal tracking control for switched linear systems with unknown dynamics. We convert the problem into an optimal control problem of the augmented switched systems. In view of the augmented systems, we propose a data driven switched linear quadratic regular algorithm for obtaining the optimal switching signal under unknown system dynamics. It is proved that the optimal switching signal will not cause Zeno behavior and can make the system stable. Besides, with the proposed algorithm, we just need to identify an autonomous system instead of the original systems, which has fewer parameters to be determined. A numerical example is given to illustrate the validity of the main results.& COPY; 2023 Elsevier Ltd. All rights reserved.

引用

页数：12

共 28 条

[1] Optimally switched linear systems [J].

Das, Tuhin ;

Mukherjee, Ranjan .

AUTOMATICA, 2008, 44 (05) :1437-1441

[2]

Giua A, 2001, IEEE DECIS CONTR P, P2472, DOI 10.1109/CDC.2001.980634

[3]

Hespanha J. P., 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304), P2655, DOI 10.1109/CDC.1999.831330

[4] Optimal Switching and Control of Nonlinear Switching Systems Using Approximate Dynamic Programming [J].

Heydari, Ali ;

Balakrishnan, Sivasubramanya N. .

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2014, 25 (06) :1106-1117

[5] Computational adaptive optimal control for continuous-time linear systems with completely unknown dynamics [J].

Jiang, Yu ;

Jiang, Zhong-Ping .

AUTOMATICA, 2012, 48 (10) :2699-2704

[6]

JOSE CG, 2006, SIAM J CONTROL OPTIM, V45, P1915

[7] ON AN ITERATIVE TECHNIQUE FOR RICCATI EQUATION COMPUTATIONS [J].

KLEINMAN, DL .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1968, AC13 (01) :114-+

[8] Reinforcement Learning and Feedback Control USING NATURAL DECISION METHODS TO DESIGN OPTIMAL ADAPTIVE CONTROLLERS [J].

Lewis, Frank L. ;

Vrabie, Draguna ;

Vamvoudakis, Kyriakos G. .

IEEE CONTROL SYSTEMS MAGAZINE, 2012, 32 (06) :76-105

[9] Basic problems in stability and design of switched systems [J].

Liberzon, D ;

Morse, AS .

IEEE CONTROL SYSTEMS MAGAZINE, 1999, 19 (05) :59-70

[10] Adaptive fixed-time hierarchical sliding mode control for switched under-actuated systems with dead-zone constraints via event-triggered strategy [J].

Liu, Shanlin ;

Niu, Ben ;

Zong, Guangdeng ;

Zhao, Xudong ;

Xu, Ning .

APPLIED MATHEMATICS AND COMPUTATION, 2022, 435

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