Adaptive fuzzy decentralized output feedback control for stochastic nonlinear large-scale systems

被引:23
|
作者
Li, Yue [1 ]
Li, Yongming [1 ]
Tong, Shaocheng [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 systems; Fuzzy adaptive decentralized control; Fuzzy state observer; Backstepping technique; Stability analysis; UNKNOWN DEAD-ZONES; TRACKING CONTROL; NEURAL-CONTROL; DELAY SYSTEMS; DESIGN; STABILIZATION;
D O I
10.1016/j.neucom.2011.11.004
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 decentralized backstepping output feedback control approach is proposed for a class of uncertain large-scale stochastic nonlinear systems without the measurements of the states. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy state observer is designed for estimating the unmeasured states. On the basis of the fuzzy state observer, and by combining the adaptive backstepping technique with decentralized control design, an adaptive fuzzy decentralized output feedback control approach is developed. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) in probability, and the observer errors and the output of the system converge to a small neighborhood of the origin by choosing appropriate design parameters. A simulation example is provided to show the effectiveness of the proposed approach. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:38 / 46
页数:9
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