Optimization of type-2 fuzzy logic controllers using PSO applied to linear plants

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

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

13 Scopus citations

Abstract

We use the Particle Swarm Optimization (PSO) method to find the parameters of the membership functions of a type-2 fuzzy logic controller (Type-2 FLC) in order to minimize the state error for linear systems. PSO is used to find the optimal Type-2 FLC to achieve regulation of the output and stability of the closed-loop system. For this purpose, we change the values of the cognitive, social and inertia variables in the PSO. Simulation results, with the optimal FLC implemented in Simulink, show the feasibility of the proposed approach.

Original languageEnglish
Title of host publicationSoft Computing for Intelligent Control and Mobile Robotics
PublisherSpringer Verlag
Pages181-193
Number of pages13
ISBN (Print)9783642155338
DOIs
StatePublished - 2010
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume318
ISSN (Print)1860-949X

Keywords

  • Fuzzy Logic Optimizations
  • PSO

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