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

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概要

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• 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 Lure 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 masters 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.

• （社）電子情報通信学会の論文
• 2008-07-01

著者

• Wu Bing

  Department Of Electrical And Control Engineering National Chiao Tung University

• Wu Bing-fei

  Department Of Electrical And Control Engineering National Chiao Tung University

• MA Li-Shan

  Department of Electrical and Control Engineering, National Chiao Tung University

• PERNG Jau-Woei

  Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-sen University

• Ma Li-shan

  Department Of Electrical And Control Engineering National Chiao Tung University

• Wu Bing‐fei

  National Chiao Tung Univ. Hsinchu Twn

• Perng Jau-woei

  Department Of Mechanical And Electro-mechanical Engineering National Sun Yat-sen University

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