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Adaptive Synchronization of Uncertain Chaotic Systems via Neural Network-Based Dynamic Surface Control Design

  • Liyou Fang
  • Tieshan Li
  • Xin Wang
  • Xiaori Gao
Conference paper
  • 3.3k Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7952)

Abstract

In this paper, the adaptive synchronization problem is investigated for a class of uncertain chaotic systems. By using the RBF networks to approximation unknown functions of the master system, an adaptive neural synchronization scheme is proposed with the combination of backstepping technique and dynamic surface control (DSC). This proposed method, similar to backstepping but with an important addition, can overcome the “explosion of complexity” of the traditional backstepping by introducing a first-order filtering. Thus, the closed-loop stability and asymptotic synchronization can be achieved. Finally, simulation results are presented to illustrate the effectiveness of the approach.

Keywords

synchronization backstepping dynamic surface neural networks chaotic system 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Liyou Fang
    • 1
  • Tieshan Li
    • 1
  • Xin Wang
    • 1
  • Xiaori Gao
    • 1
  1. 1.Navigation CollegeDalian Maritime UniversityDalianChina

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