Type-2 fuzzy logic controllers optimization using genetic algoritms and particle swarm optimization

Ricardo Martinez, Antonio Rodriguez, Oscar Castillo, Luis T. Aguilar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

28 Scopus citations

Abstract

In this paper we apply bio-inspired optimization methods to design type-2 fuzzy logic controllers (FLC) to minimize the steady state error of linear systems. We test the optimal FLC obtained by the genetic algorithms and the PSO using benchmark plants. The bio-inspired methods are used to find the parameters of the membership functions of the FLC to obtain the optimal controller. Simulation results are implemented in Simulink showing the feasibility of the proposed approach.

Original languageEnglish
Title of host publicationProceedings - 2010 IEEE International Conference on Granular Computing, GrC 2010
Pages724-727
Number of pages4
DOIs
StatePublished - 2010
Externally publishedYes
Event2010 IEEE International Conference on Granular Computing, GrC 2010 - San Jose, CA, United States
Duration: 14 Aug 201016 Aug 2010

Publication series

NameProceedings - 2010 IEEE International Conference on Granular Computing, GrC 2010

Conference

Conference2010 IEEE International Conference on Granular Computing, GrC 2010
Country/TerritoryUnited States
CitySan Jose, CA
Period14/08/1016/08/10

Keywords

  • Fuzzy logic controllers
  • Genetic algorithms
  • Particle swarm optimization

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