Using a Neural Network Controller to Control Chaos in the Rossler System

Author

Yang, Li-Xin ; Zhang, Zhong-Rong ; Zhang, Jian-Gang

Author_Institution

Sch. of Math. & Stat., Tianshui Normal Univ., Tianshui, China

Volume

3

fYear

2009

fDate

7-8 Nov. 2009

Firstpage

50

Lastpage

53

Abstract

The complex dynamics behaviors of the Rossler reaction systems are studied in the paper. By applying bifurcation diagram and phase diagram are presented to analyze periodic oscillation state and chaos motions. Periodic and chaotic motions of the system can be distinguished by Lyapunov exponent method. The chaotic motion of the system is controlled using neural network controller. We obtain the steady periodic orbit of the system under effectively controlling. It is concluded the hyperbolic tangent function is the best candidate as the threshold function of NNC for controlling the Rossler reaction system. By studying numerical simulations, it is possible to provide reliable theory and effective numerical method for other systems.

Keywords

Lyapunov methods; neurocontrollers; nonlinear control systems; Lyapunov exponent method; Rossler reaction systems; bifurcation diagram; chaos control; chaotic motion; neural network control; periodic motion; phase diagram; Artificial intelligence; Bifurcation; Chaos; Control systems; Electronic mail; Mathematics; Motion control; Neural networks; Nonlinear control systems; Nonlinear equations; Rossler system; chaos; neural network controller;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-3835-8

Electronic_ISBN

978-0-7695-3816-7

Type

conf

DOI

10.1109/AICI.2009.476

Filename

5376518