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Non-linear system control using a recurrent fuzzy neural network based on improved particle swarm optimisation.

Authors :
Cheng-Jian Lin
Chi-Yung Lee
Source :
International Journal of Systems Science. Apr2010, Vol. 41 Issue 4, p381-395. 15p. 2 Color Photographs, 10 Diagrams, 4 Charts, 8 Graphs.
Publication Year :
2010

Abstract

This article introduces a recurrent fuzzy neural network based on improved particle swarm optimisation (IPSO) for non-linear system control. An IPSO method which consists of the modified evolutionary direction operator (MEDO) and the Particle Swarm Optimisation (PSO) is proposed in this article. A MEDO combining the evolutionary direction operator and the migration operation is also proposed. The MEDO will improve the global search solution. Experimental results have shown that the proposed IPSO method controls the magnetic levitation system and the planetary train type inverted pendulum system better than the traditional PSO and the genetic algorithm methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00207721
Volume :
41
Issue :
4
Database :
Academic Search Index
Journal :
International Journal of Systems Science
Publication Type :
Academic Journal
Accession number :
49144041
Full Text :
https://doi.org/10.1080/00207720903045783