Nonlinear System Modeling Study Based on Fuzzy Neural Network with Chaotic Mechanism

Wen Li; Yu Guo

doi:10.4028/www.scientific.net/AMR.532-533.460

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 532-533Nonlinear System Modeling Study Based on Fuzzy...

Nonlinear System Modeling Study Based on Fuzzy Neural Network with Chaotic Mechanism

Abstract:

This paper for the shortcomings of conventional BP algorithm which has slow convergence and falls into local minimum easily, the nonlinear self-feedback term with chaotic mechanism is introduced into this algorithm. Thus chaotic BP algorithm (CBPA) is given. The weight of fuzzy neural network (FNN) is trained and learned by using it. Thus an introduction-type fuzzy chaotic neural network (IFCNN) is constituted. Then simulation of nonlinear system based on IFCNN given is proposed. Simulation results show that the designed IFCNN has the same and complex dynamic characteristics with chaotic system, which has good modeling capabilities for nonlinear system.

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Periodical:

Advanced Materials Research (Volumes 532-533)

Pages:

460-464

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.532-533.460

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Online since:

June 2012

Authors:

Wen Li, Yu Guo

Keywords:

Chaotic BP Algorithm Component, Fuzzy Neural Network (FNN), Nonlinear System Modeling

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