Using a Neural Network Controller to Control Chaos in the Rossler System
- Resource Type
- Conference
- Authors
- Yang, Li-Xin; Zhang, Zhong-Rong; Zhang, Jian-Gang
- Source
- 2009 International Conference on Artificial Intelligence and Computational Intelligence Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on. 3:50-53 Nov, 2009
- Subject
- Computing and Processing
Communication, Networking and Broadcast Technologies
Control systems
Neural networks
Chaos
Bifurcation
Mathematics
Electronic mail
Motion control
Nonlinear control systems
Nonlinear equations
Artificial intelligence
chaos
neural network controller
Rossler system
- Language
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.