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A hybrid optimization method with PSO and GA to automatically design Type-1 and Type-2 fuzzy logic controllers

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Abstract

In this paper we propose the use of a hybrid PSO-GA optimization method for automatic design of fuzzy logic controllers (FLC) to minimize the steady state error of a plant’s response. We test the optimal FLC obtained by the hybrid PSO-GA method using benchmark control 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 to show the feasibility of the proposed approach. A comparison is also made among the proposed Hybrid PSO-GA, GA and PSO to determine if there is a significant difference in the results.

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Authors and Affiliations

  1. School of Engineering UABC University, Tijuana, Mexico

    Ricardo Martínez-Soto & Antonio Rodriguez

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo

  3. Centro de Investigación y Desarrollo de Tecnología Digital, Instituto Politécnico Nacional, Tijuana, Mexico

    Luis T. Aguilar

Authors
  1. Ricardo Martínez-Soto
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  2. Oscar Castillo
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  3. Luis T. Aguilar
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  4. Antonio Rodriguez
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Correspondence to Oscar Castillo.

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Martínez-Soto, R., Castillo, O., Aguilar, L.T. et al. A hybrid optimization method with PSO and GA to automatically design Type-1 and Type-2 fuzzy logic controllers. Int. J. Mach. Learn. & Cyber. 6, 175–196 (2015). https://doi.org/10.1007/s13042-013-0170-8

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  • DOI: https://doi.org/10.1007/s13042-013-0170-8

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