Fuzzy-identification-based adaptive backstepping control using a self-organizing fuzzy system

Pin Cheng Chen, Chun Fei Hsu*, Tsu Tian Lee, Chi-Hsu Wang

*Corresponding author for this work

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

In this paper, a fuzzy-identification-based adaptive backstepping control (FABC) scheme is proposed. The FABC system is composed of a backstepping controller and a robust controller. The backstepping controller, which uses a self-organizing fuzzy system (SFS) with the structure and parameter learning phases to on-line estimate the controlled system dynamics, is the principal controller, and the robust controller is designed to dispel the effect of approximation error introduced by the SFS. The developed SFS automatically generates and prunes the fuzzy rules by the proposed structure adaptation algorithm and the parameters of the fuzzy rules and membership functions tunes on-line in the Lyapunov sense. Thus, the overall closed-loop FABC system can guarantee that the tracking error and parameter estimation error are uniformly ultimately bounded; and the tracking error converges to a desired small neighborhood around zero. Finally, the proposed FABC system is applied to a chaotic dynamic system to show its effectiveness. The simulation results verify that the proposed FABC system can achieve favorable tracking performance even with unknown controlled system dynamics.

Original languageEnglish
Pages (from-to)635-647
Number of pages13
JournalSoft Computing
Volume13
Issue number7
DOIs
StatePublished - 1 Jan 2009

Keywords

  • Adaptive control
  • Backstepping control
  • Chaotic dynamic system
  • Self-organizing fuzzy system
  • Structure adaptation

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