Open AccessGenetic-based neural network control for chaotic system
Author(s) -
Yaonan Wang,
Tan Wen
Publication year - 2003
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.52.2723
Subject(s) - computer science , artificial neural network , chaotic , control (management) , artificial intelligence
A novel genetic-based neural network control for chaos is presented. The method proposed has been successfully applied to control two simulated chaotic systems by incorporating the techniques of small perturbations and the periodic control in this paper. The simulation results showed that the neural network trained by genetic algorithm can learn to produce a series of small perturbations to conver t chaotic oscillations of a chaotic system into desired regular ones. The scheme requires no knowledge about the mathematical model. Moreover, the approach is r easonably robust to noise, it can be extended to control other chaotic systems.