Chaos control using maximum Lyapunov number of universal learning network

Author

Hirasawa, Kotaro ; Wan, Xiaofeng ; Murata, Junichi ; Hu, Jinglu

Author_Institution

Graduate Sch. of Inf. Sci. & Electr. Eng., Kyushu Univ., Fukuoka, Japan

Volume

2

fYear

1998

fDate

11-14 Oct 1998

Firstpage

1702

Abstract

Chaotic behaviors are characterized mainly by Lyapunov numbers of a dynamic system. In this paper, a new method is proposed, which can control the maximum Lyapunov number of dynamic system that can be represented by universal learning networks (ULNs). The maximum Lyapunov number of a dynamic system can be formulated by using higher order derivatives of ULNs and parameters of ULNs can be adjusted for the maximum Lyapunov number to approach the target value by the combined gradient and random search method. Based on simulation results, a fully connected ULN with three nodes is possible to display chaotic behaviors

Keywords

Lyapunov methods; chaos; gradient methods; learning (artificial intelligence); optimisation; recurrent neural nets; search problems; chaos control; dynamic system; gradient method; higher order derivatives; maximum Lyapunov number; random search method; recurrent neural networks; universal learning network; Biological system modeling; Chaos; Control systems; Delay effects; Displays; Information science; Multi-layer neural network; Neural networks; Neurons; Search methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on

Conference_Location

San Diego, CA

ISSN

1062-922X

Print_ISBN

0-7803-4778-1

Type

conf

DOI

10.1109/ICSMC.1998.728139

Filename

728139