Fuzzy logic controllers optimization using genetic algorithms and particle swarm optimization

Ricardo Martinez-Soto, Oscar Castillo, Luis T. Aguilar, Patricia Melin

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

29 Scopus citations

Abstract

In this paper we apply to Bio-inspired and evolutionary optimization methods to design 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 applied on linear systems using benchmark plants. The bio-inspired and the evolutionary methods are used to find the parameters of the membership functions of the FLC to obtain the optimal controller. Simulation results are obtained with Simulink showing the feasibility of the proposed approach.

Original languageEnglish
Title of host publicationAdvances in Soft Computing - 9th Mexican International Conference on Artificial Intelligence, MICAI 2010, Proceedings
Pages475-486
Number of pages12
EditionPART 2
DOIs
StatePublished - 2010
Event9th Mexican International Conference on Artificial Intelligence, MICAI 2010 - Pachuca, Mexico
Duration: 8 Nov 201013 Nov 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6438 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th Mexican International Conference on Artificial Intelligence, MICAI 2010
Country/TerritoryMexico
CityPachuca
Period8/11/1013/11/10

Keywords

  • Fuzzy Logic Controllers
  • Genetic Algorithms
  • Particle Swarm Optimization

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