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Genetic Optimization of Modular Type-1 Fuzzy Controllers for Complex Control Problems

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Soft Computing Applications in Optimization, Control, and Recognition

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 294))

Abstract

In this paper a method to design modular type-1 fuzzy controllers using genetic optimization is presented. The method is tested with a problem that requires five individual controllers. Simulation results with a genetic algorithm for optimizing the membership functions of the five individual controllers are presented. Simulation results show that the proposed modular control approach offers advantages over existing control methods.

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Author information

Authors and Affiliations

  1. Tijuana Institute of Technology, Tijuana, Mexico

    Leticia Cervantes & Oscar Castillo

Authors
  1. Leticia Cervantes
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  2. Oscar Castillo
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Editor information

Editors and Affiliations

  1. , Graduate Program of Computer Science, Tijuana Institute of Technology, Calzada Tecnologico s/n, Tijuana, 22379, Mexico

    Patricia Melin

  2. , Graduate Program of Computer Science, Tijuana Institute of Technology, Calzada Tecnologico s/n, Tijuana, 22379, Mexico

    Oscar Castillo

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Cervantes, L., Castillo, O. (2013). Genetic Optimization of Modular Type-1 Fuzzy Controllers for Complex Control Problems. In: Melin, P., Castillo, O. (eds) Soft Computing Applications in Optimization, Control, and Recognition. Studies in Fuzziness and Soft Computing, vol 294. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35323-9_6

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  • DOI: https://doi.org/10.1007/978-3-642-35323-9_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35322-2

  • Online ISBN: 978-3-642-35323-9

  • eBook Packages: EngineeringEngineering (R0)

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