Fuzzy logic controllers optimization using genetic algorithms and particle swarm optimization

Authors:
Ricardo Martinez-Soto;Oscar Castillo;Luis T. Aguilar;Patricia Melin
Affiliations:
School of Engineering, UABC University, Tijuana, México;Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, México;Centro de Investigación y Desarrollo de Tecnología Digital, Instituto Politécnico Nacional, Tijuana, México;Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, México
Venue:
MICAI'10 Proceedings of the 9th Mexican international conference on Artificial intelligence conference on Advances in soft computing: Part II
Year:
2010

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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 bioinspired 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.