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Dynamic Optimal Parameter Setting with Fuzzy Argument to Metaheuristic Algorithm Variant for Fuzzy Tracking Controllers

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Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation (INFUS 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 307))

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Abstract

In this work, we describe the evaluation between the original shark smell optimization method (SSO) and its variant (VSSO) in the dynamic adjustment of its main parameters applying T2FLS. The SSO metaheuristic was recently created, which demonstrates the diverse olfactory abilities of the shark in search of food, as inspiration. In this metaheuristic, multiple hunting cycles are used using two main movements forward and rotational twist, to establish a better equilibrium between the exploration and exploitation stages, with the aim of having a better process of searching for optimal solutions. The goal is the adjustment of the point values that form the FMs of the fuzzy system that we call (FSSO), the purpose is to obtain an optimal vector of values unlike the original SSO by performing dynamic adjustment in the parameters of the metaheuristic, in combination with salp swarm metaheuristics (SSA). The FSSO fuzzy system is tested with the proposed method with Benchmark CEC-2017 functions to see its functionality and thus enhance its behavior during different dimensions in addition to highlighting its characteristics in solving the problem in the last part of the work on the motor DC.

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Authors and Affiliations

  1. Tijuana Institute of Technology, Tijuana, 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 authors

Correspondence to Felizardo Cuevas , Oscar Castillo or Prometeo Cortes-Antonio .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Industrial Engineering Department, Yildiz Technical University, Istanbul, Turkey

    Selcuk Cebi

  3. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Sezi Cevik Onar

  4. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Basar Oztaysi

  5. Industrial Engineering Department, Galatasaray University, Istanbul, Turkey

    A. Cagri Tolga

  6. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Irem Ucal Sari

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Cuevas, F., Castillo, O., Cortes-Antonio, P. (2022). Dynamic Optimal Parameter Setting with Fuzzy Argument to Metaheuristic Algorithm Variant for Fuzzy Tracking Controllers. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A.C., Sari, I.U. (eds) Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation. INFUS 2021. Lecture Notes in Networks and Systems, vol 307. Springer, Cham. https://doi.org/10.1007/978-3-030-85626-7_62

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