A novel learning-based asynchronous sliding mode control for discrete-time semi-Markov jump systems

被引：43

作者：

Li, Fanbiao ^{[1
,2
]}

Wu, Zheng ^{[1
]}

Yang, Chunhua ^{[1
]}

Shi, Yang ^{[3
]}

Huang, Tingwen ^{[4
]}

Gui, Weihua ^{[1
]}

机构：

[1] Cent South Univ, Sch Automat, Changsha 410083, Peoples R China

[2] Peng Cheng Lab, Shenzhen 518000, Peoples R China

[3] Univ Victoria, Dept Mech Engn, Victoria, BC V8W 3P6, Canada

[4] Texas A&M Univ Qatar, POB 23874, Doha, Qatar

来源：

AUTOMATICA | 2022年 / 143卷

基金：

中国国家自然科学基金;

关键词：

Sliding mode; Learning-based control; Discrete-time semi-Markov jump systems; Asynchronous switch; STABILITY;

D O I：

10.1016/j.automatica.2022.110428

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a novel asynchronous sliding mode-based learning control is proposed for a class of discrete-time semi-Markov jump systems, in which the probability density function of sojourn-time is dependent on two consecutive modes. The asynchronous switching characteristic is employed for the nonsynchronization between the controller and the jump modes. Based on the discrete-time semi-Markov kernel and multiple-Lyapunov functions, sufficient conditions are provided to guarantee the alpha-error mean-square stability of the sliding mode dynamics. Furthermore, a recursive sliding mode learning controller is designed such that the sliding modes can be driven onto the designed sliding surface and the chattering caused by the asynchronous switching and mode jump can be effectively suppressed. Finally, numerical simulations on the continuous stirred tank reactor system are given to demonstrate the effectiveness and potential of the proposed techniques. (C) 2022 Elsevier Ltd. All rights reserved.

引用

页数：8

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