Decentralized adaptive control of large-scale nonaffine nonlinear systems using radial basis function neural networks

被引：10

作者：

Karimi, Bahram ^{[1
]}

Menhaj, Mohammad Bagher ^{[1
]}

Saboori, Iman ^{[1
]}

机构：

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

来源：

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES | 2007年 / E90A卷 / 10期

关键词：

adaptive control; decentralized nonaffine nonlinear system; radial basis neural network (RBNN);

D O I：

10.1093/ietfec/e90-a.10.2239

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a novel decentralized adaptive neural network controller is proposed for a class of large-scale nonlinear systems with unknown nonlinear, nonaffine subsystems and unknown nonlinear interconnections. The stability of the closed loop system is guaranteed by introducing a robust adaptive bound based on Lyapunov stability analysis. A radial-basis function type neural network is used in the paper. To show the effectiveness of the proposed method, we performed some simulation studies. The results of simulation become very promising.

引用

页码：2239 / 2247

页数：9

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