An Observer-Based Neural Network Controller for Chaotic Lorenz System

Authors:
Suwat Kuntanapreeda
Affiliations:
Research and Development Center for Intelligent Systems Faculty of Engineering, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand 10800
Venue:
ISICA '08 Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence
Year:
2008

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Abstract

The paper proposes an alternative control design for the chaotic Lorenz system based on neural networks. The controller is a feedforward neural network trained by a model reference technique. Implementation of the control design requires system states for feedback, while in most of practical applications only the system output is available. To overcome this problem, a nonlinear observer is used to estimate the states of the system. Simulation results have illustrated the feasibility and effectiveness of the proposed observer-based neural network controller.