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Intelligent Backstepping Control for Chaotic Systems Using Self-Growing Fuzzy Neural Network

  • Chih-Min Lin
  • Chun-Fei Hsu
  • I-Fang Chung
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 344)

Abstract

This paper proposes an intelligent backstepping control (IBC) for the chaotic systems. The IBC system is comprised of a neural backstepping controller and a robust compensation controller. The neural backstepping controller containing a self-growing fuzzy neural network (SGFNN) identifier is the principal controller, and the robust compensation controller is designed to dispel the effect of minimum approximation error introduced by the SGFNN identifier. Finally, simulation results verify that the IBC system can achieve favorable tracking performance.

Keywords

Membership Function Chaotic System Fuzzy Rule Fuzzy Neural Network Online Learning Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chih-Min Lin
    • 1
  • Chun-Fei Hsu
    • 2
  • I-Fang Chung
    • 3
  1. 1.Department of Electrical EngineeringYuan-Ze UniversityChung-Li, Tao-YuanTaiwan, Republic of China
  2. 2.Department of Electrical and Control EngineeringNational Chiao-Tung UniversityHsinchuTaiwan, Republic of China
  3. 3.Institute of BioinformaticsNational Yang-Ming UniversityTaipeiTaiwan, Republic of China

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