Output Constrained Adaptive Controller Design for Nonlinear Saturation Systems

被引：0

作者：

Yongliang Yang ^{[1
,2
]}

Zhijie Liu ^{[1
,2
]}

Qing Li ^{[2
]}

Donald CWunsch ^{[1
,3
]}

机构：

[1] IEEE

[2] the Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing

[3] the Department of Electrical and Computer Engineering, Missouri University of Science and Technology

来源：

IEEE/CAAJournalofAutomaticaSinica | 2021年 / 8卷 / 02期

关键词：

D O I：

暂无

中图分类号：

TP13 [自动控制理论];

学科分类号：

0711 ; 071102 ; 0811 ; 081101 ; 081103 ;

摘要：

This paper considers the adaptive neuro-fuzzy control scheme to solve the output tracking problem for a class of strict-feedback nonlinear systems. Both asymmetric output constraints and input saturation are considered. An asymmetric barrier Lyapunov function with time-varying prescribed performance is presented to tackle the output-tracking error constraints. A high-gain observer is employed to relax the requirement of the Lipschitz continuity about the nonlinear dynamics. To avoid the "explosion of complexity", the dynamic surface control(DSC) technique is employed to filter the virtual control signal of each subsystem. To deal with the actuator saturation, an additional auxiliary dynamical system is designed.It is theoretically investigated that the parameter estimation and output tracking error are semi-global uniformly ultimately bounded. Two simulation examples are conducted to verify the presented adaptive fuzzy controller design.

引用

页码：441 / 454

页数：14

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