Adaptive fuzzy output-feedback dynamic surface control of MIMO switched nonlinear systems with unknown gain signs

被引:28
|
作者
Long, Lijun [1 ,2 ]
Zhao, Jun [1 ,2 ]
机构
[1] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang, Peoples R China
[2] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China
基金
中国国家自然科学基金;
关键词
Adaptive fuzzy control; Multi-input and multi-output (MIMO); Switched nonlinear systems; Switched observer; Dynamic surface control; H-INFINITY CONTROL; TRACKING CONTROL; NEURAL-CONTROL; DELAY SYSTEMS; DEAD-ZONES; STABILITY; DESIGN; STABILIZATION;
D O I
10.1016/j.fss.2015.12.006
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper investigates the problem of adaptive fuzzy tracking control for a class of multi-input multi-output (MIMO) switched uncertain nonlinear systems with unknown gain signs and unmeasurable states. Fuzzy logic systems are used to approximate the unknown nonlinear functions, a fuzzy MIMO switched observer is designed to estimate the unmeasurable states. The Nussbaum type functions are utilized to handle the unknown gain signs of the system under study. A switched-dynamic-surface-based adaptive fuzzy control approach is then established by exploiting the average dwell time method and backstepping and the dynamic surface control technique, which constructs multiple switched first -order filters to overcome the multiple "explosion of complexity" problem when applying the backstepping recursive design scheme. Also, the proposed approach extends the classical dynamic surface control technique from its original non-switched nonlinear version to a switched nonlinear version. It is proved that all the signals in the closed -loop system are semiglobal uniformly ultimately boundedness under a class of switching signals with average dwell time, and the tracking errors converge to a small neighborhood of the origin. A mass spring damper system with controller switching as a practical example is provided to demonstrate the effectiveness of the proposed design method. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:27 / 51
页数:25
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