Stabilization of unknown nonlinear systems using neural networks

被引：14

作者：

Fourati, Fathi ^{[1
]}

Chtourou, Mohamed ^{[1
]}

Kamoun, Mohamed ^{[2
]}

机构：

[1] Natl Sch Engn Sfax, Intelligent Control Optimizat & Design Complex Sy, ICOS, Sfax 3038, Tunisia

[2] Natl Sch Engn Sfax, Automat Control Unit, UCA, Sfax 3038, Tunisia

来源：

APPLIED SOFT COMPUTING | 2008年 / 8卷 / 02期

关键词：

stabilization; nonlinear systems; neural networks; state variables; optimization;

D O I：

10.1016/j.asoc.2007.04.002

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper deals with stabilization of unknown nonlinear systems using a nonlinear controller made with a backpropagation neural network. Control strategies based on an inverse state neural model built from an off-line learning step are proposed. The proposed strategies can be implemented following two approaches. The first one consists on computing control horizon based on actual state vector and desired one at a future instant. The second approach applies control action in the sense of a receding horizon. Adaptive control has been considered where the updating of the neural controller is accomplished to optimize different control objectives. (C) 2007 Elsevier B. V. All rights reserved.

引用

页码：1121 / 1130

页数：10

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