Fuzzy Neural Network Based Predictive Control of Chaotic Nonlinear Systems

Jong Tae CHOI  Yoon Ho CHOI  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E87-A   No.5   pp.1270-1279
Publication Date: 2004/05/01
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Neural Networks and Bioengineering
chaos control,  chaotic systems,  predictive control,  prediction,  fuzzy neural networks,  

Full Text: PDF(576.2KB)>>
Buy this Article

In this paper, we present a predictive control method, based on Fuzzy Neural Network (FNN), for the control of chaotic systems without precise mathematical models. In our design method, the parameters of both predictor and controller are tuned by a simple gradient descent scheme, and the weight parameters of the FNN are determined adaptively throughout system operations. In order to design the predictive controller effectively, we describe the computing procedure for each of the two important parameters. In addition, we introduce a projection matrix for determining the control input, which decreases the control performance function very rapidly. Finally, we depict various computer simulations on two representative chaotic systems (the Duffing and Hénon systems) so as to demonstrate the effectiveness of the new chaos control method.