Adaptive fuzzy control of switched nonlinear systems with uncertain dead-zone: A mode-dependent fuzzy dead-zone model

被引：19
|
作者：
Chen, Yanxian [1 ,2 ]
Liu, Zhi [1 ,2 ]
Chen, C. L. Philip [3 ]
Zhang, Yun [1 ,2 ]
机构：
[1] Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China
[2] Guangdong HongKong Macao Joint Lab Smart Discrete, Guangzhou 510006, Peoples R China
[3] South China Univ Technol, Fac Comp Sci & Engn, Guangzhou 510006, Guangdong, Peoples R China
来源：
NEUROCOMPUTING | 2021年 / 432卷
基金：
中国国家自然科学基金;
关键词：
Switched nonlinear systems; Mode-dependent fuzzy dead-zone model; Multiple Lyapunov function; Adaptive fuzzy control; OUTPUT-FEEDBACK CONTROL; TRACKING CONTROL; NEURAL-CONTROL; APPROXIMATION;
D O I：
10.1016/j.neucom.2020.12.044
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, an adaptive fuzzy control scheme is addressed for switched nonlinear systems with uncertain dead-zone, unknown nonlinearities and immeasurable states. A novel proposed mode-dependent fuzzy dead-zone model (MFDM) can not only describe the uncertain dead-zone, but also overcome the common fuzzy dead-zone model (CFDM) problems caused by disconnected parameters and conservativeness. The unknown functions are approximated by fuzzy logic systems. To estimate the immeasurable states, a switched fuzzy state observer is constructed. By using multiple Lyapunov function and defuzzifying for MFDM, a new mode-dependent fuzzy controller is proposed to assure the boundedness of the closed-loop system and the desired tracking performance. The feasibility of the presented control technique is proved by simulation examples. (c) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码：133 / 144
页数：12
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