A systematic method for design of multivariable fuzzy logic control systems

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Abstract

This paper proposes a systematic method to design a multivariable fuzzy logic controller (SMFLC) for large-scale nonlinear systems. In designing a fuzzy logic controller, the major task is to determine fuzzy rule bases, membership functions of input/output variables, and input/output scaling factors. In this work, the fuzzy rule base is generated by a rule-generated function, which is based on the negative gradient of a system performance index, the membership functions of isosceles triangle of input/output variables are fixed in the same cardinality and only the input/output scaling factors are generated from a genetic algorithm based on a fitness function. As a result, the searching space of parameters is narrowed down to a small space, the multivariable fuzzy logic controller can quickly constructed, and the fuzzy rules and the scaling factors can easily be determined. The performance of the proposed method is examined by computer simulations on a Puma 560 system and a two-inverted pendulum system.

Original languageEnglish
Pages (from-to)741-752
Number of pages12
JournalIEEE Transactions on Fuzzy Systems
Volume7
Issue number6
DOIs
Publication statusPublished - 1999 Dec 1

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Keywords

  • Fuzzy control
  • Genetic algorithm

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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