Fuzzy modeling and control based on maximum entropy self-organizing nets and cell state mapping

Jiann Horng Lin, Can Isik

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

2 Scopus citations

Abstract

A method for the systematic design of a fuzzy model is developed for the control of complex systems. The proposed fuzzy controller design is based on a maximum entropy self-organizing net (MESON) and the cell state mapping approach. For fuzzy model identification, we present an approach to constructing a self-organizing fuzzy identifier. The proposed identifier is built on a neuro-fuzzy system consisting of a maximum entropy self-organizing net and a radial basis function network. We develop the corresponding self-organizing algorithms. To design a fuzzy controller, the proposed method combines the concept of cell state mapping with the synthesis techniques of MESON used in the fuzzy model identification.

Original languageEnglish (US)
Title of host publicationAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
PublisherIEEE Computer Society
Pages45-50
Number of pages6
StatePublished - 1997
EventProceedings of the 1997 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'97 - Syracuse, NY, USA
Duration: Sep 21 1997Sep 24 1997

Other

OtherProceedings of the 1997 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'97
CitySyracuse, NY, USA
Period9/21/979/24/97

ASJC Scopus subject areas

  • Computer Science(all)
  • Media Technology

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    Lin, J. H., & Isik, C. (1997). Fuzzy modeling and control based on maximum entropy self-organizing nets and cell state mapping. In Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS (pp. 45-50). IEEE Computer Society.