Control of nonlinear systems using a self-organising neural network

被引：6

作者：

Delgado, A ^{[1
]}

机构：

[1] Univ Nacl Colombia, Dept Elect & Elect Engn, Bogota, Colombia

来源：

NEURAL COMPUTING & APPLICATIONS | 2000年 / 9卷 / 02期

关键词：

chemotaxis; input/output linearisation; linear splines; nonlinear systems; optimal control; self organising maps;

D O I：

10.1007/s005210070022

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Two applications of Self Organizing Map (SOM) networks in the context of nonlinear control are introduced, one in approximate feedback linearisation and the second in optimal control. It is shown that a modified SOM can be used to approximately Input/Output (I/O) linearise and to control nonlinear systems using a combination of the SOM learning algorithm, and a biologically inspired optimisation algorithm known as chemotaxis. A proof to guarantee the stability of the closed loop during the training of the network and the operation of the whole system is included. The results are illustrated with simulations of a single link manipulator.

引用

页码：113 / 123

页数：11

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