A Stable Neural Network-Based Controller for Class of Nonlinear Systems

被引：2

作者：

Yadmellat, P. ^{[2
]}

Samiei, E. ^{[2
]}

Talebi, H. A. ^{[1
]}

机构：

[1] Amirkabir Univ Technol, Dept Elect Engn, Tehran, Iran

[2] Amirkabir Univ Technol, Tehran, Iran

来源：

2009 IEEE CONTROL APPLICATIONS CCA & INTELLIGENT CONTROL (ISIC), VOLS 1-3 | 2009年

关键词：

ADAPTIVE-CONTROL;

D O I：

10.1109/CCA.2009.5281011

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 novel method to solve the stabilization problem for a class of nonlinear affine single-input systems using neural networks is proposed in this paper. The controller is based on feedback linearization where the control signal is directly estimated by a nonlinear in parameter neural network (NLPNN). A modified Back Propagation (BP) algorithm with e-modification is used to update the weights of the network. The stability of overall closed-loop system is shown using Lyapunov method. To evaluate the performance of the proposed controller, a set of simulations is performed on a Bossier chaotic system.

引用

页码：926 / +

页数：3

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