Synthetic adaptive fuzzy tracking control for MIMO uncertain nonlinear systems with disturbance observer

被引：10

作者：

Cui, Yang ^{[1
]}

Zhang, Huaguang ^{[1
]}

Qu, Qiuxia ^{[1
]}

Luo, Chaomin ^{[2
]}

机构：

[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China

[2] Univ Detroit Mercy, Dept Elect & Comp Engn, Adv Mobil Lab, Detroit, MI 48221 USA

来源：

NEUROCOMPUTING | 2017年 / 249卷

基金：

中国国家自然科学基金;

关键词：

Dynamic surface control (DSC); Generalized fuzzy hyperbolic model (GFHM); Nonlinear systems; Serial-parallel estimation model; Disturbance observer; DYNAMIC SURFACE CONTROL; OUTPUT-FEEDBACK CONTROL; NEURAL-NETWORKS; TRIANGULAR STRUCTURE; UNMODELED DYNAMICS; STABILITY ANALYSIS; DEAD-ZONE; DESIGN; DELAYS; MODEL;

D O I：

10.1016/j.neucom.2017.03.064

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, a synthetic adaptive fuzzy tracking control method is studied for a class of multi-input multi-output (MIMO) uncertain nonlinear systems with time-varying disturbances. The unknown nonlinear functions are approximated by employing generalized fuzzy hyperbolic model. A synthetic adaptive fuzzy control is designed by dynamic surface control, serial-parallel estimation model and the disturbance observer. Then by using Lyapunov stability theory, it is guaranteed that all the variables of the closed-loop systems are semi-globally uniformly ultimately bounded (SGUUB). Finally, a satisfactory tracking performance with faster and higher accuracy can be obtained by adjusting the parameters appropriately. A practical example simulation can demonstrate the effectiveness and applicability of the proposed control approach. (C) 2017 Elsevier B.V. All rights reserved.

引用

页码：191 / 201

页数：11

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