Globally adaptive asymptotic tracking control of nonlinear systems using nonlinearly parameterized fuzzy approximator

被引：24

作者：

Wang, Maoli ^{[1
,2
]}

Zhang, Zhengqiang ^{[3
]}

机构：

[1] Natl Supercomp Ctr Jinan, Shandong Comp Sci Ctr, Jinan 250014, Peoples R China

[2] Shandong Prov Key Lab Comp Networks, Jinan 250014, Peoples R China

[3] Qufu Normal Univ, Sch Engn, Rizhao 276826, Peoples R China

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2015年 / 352卷 / 07期

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

FEEDBACK SYSTEMS; NEURAL-CONTROL; TIME DELAYS; ACCURACY;

D O I：

10.1016/j.jfranklin.2015.04.011

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, the problem of globally stable adaptive fuzzy tracking control is addressed for a class of uncertain nonlinear systems in the canonical form. Instead of linearly parameterized fuzzy logic system (FLS), nonlinearly parameterized FLS is used to approximate the unknown nonlinear function. By combining the new parametrization of Gaussian membership function and the signal replacement approach, a novel adaptive fuzzy controller is designed. It is shown that all signals in the closed-loop system are globally bounded and that the tracking error converges to zero asymptotically. A simulation example is included to illustrate the effectiveness of the proposed approach. (C) 2015 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：2783 / 2795

页数：13

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