Integrating design stages of fuzzy systems using genetic algorithms

Michael A. Lee, Hideyuki Takagi

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

277 Citations (Scopus)

Abstract

This paper proposes an automatic fuzzy system design method that uses a Genetic Algorithm and integrates three design stages; our method determines membership functions, the number of fuzzy rules, and the rule-consequent parameters at the same time. Because these design stages may not be independent, it is important to consider them simultaneously to obtain optimal fuzzy systems. The method includes a genetic algorithm and a penalty strategy that favors systems with fewer rules. The proposed method is applied to the classic inverted pendulum control problem and has been shown to be practical through a comparison with another method.

Original languageEnglish
Title of host publication1993 IEEE International Conference on Fuzzy Systems
PublisherPubl by IEEE
Pages612-617
Number of pages6
ISBN (Print)0780306155
Publication statusPublished - Jan 1 1993
Externally publishedYes
EventSecond IEEE International Conference on Fuzzy Systems - San Francisco, CA, USA
Duration: Mar 28 1993Apr 1 1993

Publication series

Name1993 IEEE International Conference on Fuzzy Systems

Other

OtherSecond IEEE International Conference on Fuzzy Systems
CitySan Francisco, CA, USA
Period3/28/934/1/93

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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  • Cite this

    Lee, M. A., & Takagi, H. (1993). Integrating design stages of fuzzy systems using genetic algorithms. In 1993 IEEE International Conference on Fuzzy Systems (pp. 612-617). (1993 IEEE International Conference on Fuzzy Systems). Publ by IEEE.