Discrete-time adaptive control of nonlinear systems using neural networks

被引：0

作者：

Fabri, SG ^{[1
]}

Kadirkamanathan, V ^{[1
]}

机构：

[1] Univ Sheffield, Dept Automat Control & Syst Engn, Sheffield S1 3JD, S Yorkshire, England

来源：

ADAPTIVE SYSTEMS IN CONTROL AND SIGNAL PROCESSING 1998 | 2000年

关键词：

discrete-time systems; adaptive control; neural networks; nonlinear control; Lyapunov stability;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A neural-adaptive control system for a class of discrete-time nonlinear plants is proposed. Neural networks and adaptation are required to ensure stability and asymptotic convergence of the tracking error, in spite of the nonlinear and unknown plant dynamics. An augmented error adaptive approach is taken. The effect of the inevitable imperfect approximation accuracy of the neural network on system stability is taken into consideration by using dead-zone adaptation. Stability and convergence proofs are presented together with a simulation example. Copyright (C) 1998 IFAC.

引用

页码：121 / 126

页数：6

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