Fault-tolerant control for stochastic multi-agent systems with output constraints

被引：1
|
作者：
Zheng X.-H. [1 ]
Dong G.-W. [1 ]
Zhou Q. [1 ]
Lu R.-Q. [1 ]
机构：
[1] Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control, Guangdong University of Technology, Guangzhou, 510006, Guangdong
来源：
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2020年 / 37卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Fault-tolerant control; Multi-agent systems; Nonstrict-feedback form; Output constraints; Stochastic systems;
D O I：
10.7641/CTA.2019.90376
中图分类号：
学科分类号：
摘要：
In this paper, the adaptive neural network fault-tolerant control strategy is proposed for a class of nonstrictfeedback stochastic multi-agent systems with output constraints and actuator faults under a directed communication topology. Neural networks are utilized to approximate unknown nonlinear functions. Furthermore, the barrier Lyapunov function is employed to deal with the problem of output constraints. Combining backstepping method, dynamic surface control technique and Nussbaum function, an adaptive neural network fault-tolerant control method is proposed. Based on Lyapunov stability theory, it is proved that all followers' outputs can be consistent with the leader's output. All signals in the closedloop systems are semiglobally uniform ultimate bounded in probability and the output of systems can be limited within the given compact set. Finally, the effectiveness of the proposed control scheme is verified through numerical simulation. © 2020, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
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收藏
页码：961 / 968
页数：7
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