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Observer-Based Synchronization for a Class of Unknown Chaos Systems with Adaptive Fuzzy-Neural Network

Bing-Fei WU, Li-Shan MA, Jau-Woei PERNG

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Summary :

This investigation applies the adaptive fuzzy-neural observer (AFNO) to synchronize a class of unknown chaotic systems via scalar transmitting signal only. The proposed method can be used in synchronization if nonlinear chaotic systems can be transformed into the canonical form of Lur'e system type by the differential geometric method. In this approach, the adaptive fuzzy-neural network (FNN) in AFNO is adopted on line to model the nonlinear term in the transmitter. Additionally, the master's unknown states can be reconstructed from one transmitted state using observer design in the slave end. Synchronization is achieved when all states are observed. The utilized scheme can adaptively estimate the transmitter states on line, even if the transmitter is changed into another chaos system. On the other hand, the robustness of AFNO can be guaranteed with respect to the modeling error, and external bounded disturbance. Simulation results confirm that the AFNO design is valid for the application of chaos synchronization.

Publication
IEICE TRANSACTIONS on Fundamentals Vol.E91-A No.7 pp.1797-1805
Publication Date
2008/07/01
Publicized
Online ISSN
1745-1337
DOI
10.1093/ietfec/e91-a.7.1797
Type of Manuscript
PAPER
Category
Language, Thought, Knowledge and Intelligence

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