Robust adaptive NN feedback linearization control of nonlinear systems

被引：44

作者：

Ge, SS

机构：

[1] Department of Electrical Engineering, National University of Singapore, 0511

来源：

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE | 1996年 / 27卷 / 12期

关键词：

D O I：

10.1080/00207729608929339

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, a robust adaptive neural network feedback linearization control law is presented for a class of nonlinear dynamic systems. First, the 'GL' matrices and the corresponding operator are introduced, which brings a new methodology into the analysis of neural networks. Secondly, the basic ideas of Feedback Linearization Control (FLC) of nonlinear systems are discussed. Finally, a robust adaptive neural network FLC of nonlinear systems is presented. It is shown that uniformly stable adaptation is assured and asymptotic tracking is achieved if Bounded Basis Functions (BBF) are used, and output tracking errors also converge to zero.

引用

页码：1327 / 1338

页数：12

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