Backstepping nonlinear control using nonlinear parametric fuzzy systems

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Based on nonlinear parametric fuzzy systems, an adaptive backstepping controller is proposed for a class of strict-feedback nonlinear systems. The nonlinear parametric fuzzy systems are capable of automatically learning their membership functions and tuning their weightings. Since the adjustable parameters of the membership functions nonlinearly appear in the fuzzy systems, the adaptive laws are derived by estimating the derivative of the fuzzy systems. Moreover, the stability of the closed-loop system is analyzed by means of Lyapunov theory, and some tracking performance is guaranteed. Finally, two examples are provided to demonstrate the effectiveness and applicability of the proposed scheme.

Original languageEnglish
Pages (from-to)225-231
Number of pages7
JournalInternational Journal of Fuzzy Systems
Volume11
Issue number4
Publication statusPublished - 2009 Dec

Fingerprint

Backstepping Control
Backstepping
Nonlinear Control
Fuzzy systems
Fuzzy Systems
Membership functions
Membership Function
Lyapunov Theory
Feedback Systems
Closed loop systems
Closed-loop System
Weighting
Nonlinear systems
Tuning
Nonlinear Systems
Derivatives
Feedback
Controller
Derivative
Controllers

Keywords

  • Backstepping design
  • Fuzzy control
  • Nonlinear control

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Computational Theory and Mathematics
  • Theoretical Computer Science

Cite this

Backstepping nonlinear control using nonlinear parametric fuzzy systems. / Leu, Yih Guang.

In: International Journal of Fuzzy Systems, Vol. 11, No. 4, 12.2009, p. 225-231.

Research output: Contribution to journalArticle

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