Adaptive backstepping fuzzy control for a class of nonlinear systems

Yih Guang Leu*, Jian You Lin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

By using a nonlinear parametric fuzzy identifier, an adaptive backstepping controller is proposed for a class of nonlinear systems. The nonlinear parametric fuzzy identifier is capable of automatically learning its membership functions. Since the fuzzy identifier is highly nonlinear, the derivative computation burden is enormous. Thus, this paper uses an estimation technique to effectively alleviate the derivative computation burden, and demonstrates the applicability of the proposed scheme by using computer simulation.

Original languageEnglish
Title of host publicationAdvances in Neural Networks - ISNN 2009 - 6th International Symposium on Neural Networks, ISNN 2009, Proceedings
Pages1123-1129
Number of pages7
EditionPART 2
DOIs
Publication statusPublished - 2009
Event6th International Symposium on Neural Networks, ISNN 2009 - Wuhan, China
Duration: 2009 May 262009 May 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5552 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Symposium on Neural Networks, ISNN 2009
Country/TerritoryChina
CityWuhan
Period2009/05/262009/05/29

Keywords

  • Backstepping design
  • Fuzzy control
  • Nonlinear control

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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