Observer-based synchronization for a class of unknown chaos systems with adaptive fuzzy-neural network

Bing-Fei Wu*, Li Shan Ma, Jau Woei Perng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)1797-1805
Number of pages9
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number7
StatePublished - 1 Jan 2008


  • Adaptive fuzzy-neural observer (AFNO)
  • Chaos
  • Fuzzy-neural network (FNN)
  • Robust
  • Synchronization


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