Adaptive fuzzy backstepping output feedback control for a class of uncertain stochastic nonlinear system in pure-feedback form

被引:25
作者
Gao, Yang [1 ]
Tong, Shaocheng [1 ]
Li, Yongming [1 ]
机构
[1] Liaoning Univ Technol, Dept Basic Math, Jinzhou 121000, Liaoning, Peoples R China
基金
中国国家自然科学基金;
关键词
Stochastic nonlinear pure-feedback systems; Backstepping technique; State observer; Adaptive fuzzy control; DYNAMIC SURFACE CONTROL; DISTURBANCE OBSERVER; NEURAL-NETWORK; STABILIZATION; DESIGN; DELAYS;
D O I
10.1016/j.neucom.2013.06.036
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper is concerned with the problem of adaptive fuzzy output feedback for a class of uncertain stochastic pure-feedback nonlinear systems with immeasurable states. With the help of fuzzy logic systems to approximate the unknown nonlinear functions, and a fuzzy state observer is designed to estimate the unmeasured states. By incorporating the filtered signals into the backstepping recursive design, a fuzzy adaptive output feedback control scheme is developed. It is proven that all the signals of the closed-loop system are bounded in probability, and also that the observer errors and the output of the system converge to a small neighborhood of the origin by appropriate choice of the design parameters. Simulation studies are included to illustrate the effectiveness of the proposed approach. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:126 / 133
页数:8
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