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Genetic Algorithm Optimization for Type-2 Non-singleton Fuzzy Logic Controllers

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Recent Advances on Hybrid Approaches for Designing Intelligent Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 547))

Abstract

In this chapter we study the automatic design of type-2 non-singleton fuzzy logic controller. To test the controller we use an autonomous mobile robot for the trajectory tracking control. We take the basis of the interval type-2 fuzzy logic controller of previous work for the extension to the type-2 non-singleton fuzzy logic controller. A genetic algorithm is used to obtain an automatic design of the type-2 non-singleton fuzzy logic controller (NSFLC). Simulation results are obtained with Simulink showing the behavior of the mobile robot whit this type of controller.

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Author information

Authors and Affiliations

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

    Ricardo Martínez-Soto & Oscar Castillo

  2. School of Engineering UABC University, Tijuana, Mexico

    Juan R. Castro

Authors
  1. Ricardo Martínez-Soto
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  2. Oscar Castillo
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  3. Juan R. Castro
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Corresponding author

Correspondence to Ricardo Martínez-Soto .

Editor information

Editors and Affiliations

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

    Oscar Castillo

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

    Patricia Melin

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada

    Witold Pedrycz

  4. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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Martínez-Soto, R., Castillo, O., Castro, J.R. (2014). Genetic Algorithm Optimization for Type-2 Non-singleton Fuzzy Logic Controllers. In: Castillo, O., Melin, P., Pedrycz, W., Kacprzyk, J. (eds) Recent Advances on Hybrid Approaches for Designing Intelligent Systems. Studies in Computational Intelligence, vol 547. Springer, Cham. https://doi.org/10.1007/978-3-319-05170-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-05170-3_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05169-7

  • Online ISBN: 978-3-319-05170-3

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