Adaptive synchronization for unknown chaotic systems with fuzzy-neural network observer

Abstract

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 proposed approach, the receiver states can be reconstructed from one transmitted state using AFNO design. The adaptive fuzzy-niural network (INN) in AFNO is adopted to model the nonlinear term in the transmitter. Additionally, an observer is designed to estimate the other states of the master. Synchronization is achieved when all states are observed. The proposed scheme can adaptively estimated the transmitter states using AFNO, even if the transmitter changes into another chaotic system. Simulation results confirm that the proposed AFNO design is valid.