Adaptive fuzzy fixed-time control for a class of strict-feedback stochastic nonlinear systems

被引：0
|
作者：
Wang, Nan [1 ,2 ]
Fu, Zhumu [1 ,2 ]
Tao, Fazhan [1 ,2 ]
Song, Shuzhong [1 ,2 ]
Ma, Min [3 ]
机构：
[1] College of Information Engineering, Henan University of Science and Technology, Henan, Luoyang, China
[2] Key Laboratory of Robot and Intelligent System of Henan Province, Henan University of Science and Technology, Henan, Luoyang, China
[3] Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Heilongjiang, Harbin, China
来源：
Systems Science and Control Engineering | 2022年 / 10卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Fuzzy logic - Fuzzy control - Feedback - Adaptive control systems - Nonlinear systems - Stochastic control systems - Stochastic systems;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper studies fixed-time tracking problems for stochastic nonlinear systems in strict-feedback form. Different from previous results, the practical fixed-time bounded theorem for stochastic nonlinear systems is given. The unknown functions of the stochastic nonlinear systems are approximated by the Fuzzy logic system (FLS) which has a universal approximation. Then by using a back-stepping method, a novel adaptive fuzzy fixed-time controller is designed for stochastic nonlinear systems based on the fixed-time bounded theorem. The states of the stochastic nonlinear systems are guaranteed to converge into an equilibrium point contained compact set semi-globally in fixed-time by the designed controller. Finally, a numerical example and a vehicle tracking model example are provided to illustrate the proposed strategy. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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页码：142 / 153
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