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Optimal Design of Interval Type-2 Fuzzy Tracking Controllers of Mobile Robots Using a Metaheuristic Algorithm

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Recent Advances of Hybrid Intelligent Systems Based on Soft Computing

Part of the book series: Studies in Computational Intelligence ((SCI,volume 915))

Abstract

This paper describes a modification of a biological inspired algorithm based on shark behavior, the Shark Smell Optimization (SSO), for the optimization of the membership functions parameters for the fuzzy controllers of autonomous mobile robots. SSO is a metaheuristic technique based on the behavior presented by sharks in nature, which can be used for solving optimization problems. First, SSO is used to optimize benchmark control problems. Second, the traditional SSO is tested with the optimization of the membership function’s parameters of type-1 fuzzy controllers. Third, tests are also performed with the Interval Type-2 Fuzzy Logic Controller. The comparison of results between the controller optimized with SSO and the controller optimized with WDO demonstrates that the proposed method shows better performance in the optimal design of fuzzy controllers.

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Authors and Affiliations

  1. Tijuana Institute of Technology, Tijuana, BC, Mexico

    Felizardo Cuevas, Oscar Castillo & Prometeo Cortes-Antonio

Authors
  1. Felizardo Cuevas
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  2. Oscar Castillo
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  3. Prometeo Cortes-Antonio
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Corresponding author

Correspondence to Oscar Castillo .

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Editors and Affiliations

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

    Patricia Melin

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

    Oscar Castillo

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

    Janusz Kacprzyk

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Cuevas, F., Castillo, O., Cortes-Antonio, P. (2021). Optimal Design of Interval Type-2 Fuzzy Tracking Controllers of Mobile Robots Using a Metaheuristic Algorithm. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Recent Advances of Hybrid Intelligent Systems Based on Soft Computing. Studies in Computational Intelligence, vol 915. Springer, Cham. https://doi.org/10.1007/978-3-030-58728-4_18

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