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Optimization of Fuzzy Trajectory Tracking in Autonomous Mobile Robots Based on Bio-inspired Algorithms

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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

In this paper a comparison between the Bee Colony Optimization (BCO) and the Chicken Search Optimization (CSO) algorithms in optimal fuzzy control design is presented. The comparison is based on solving the problem to find the optimal distribution on the Membership Functions (MFs) of fuzzy controllers for mobile robots. Optimization in the structure and parameters for designing for a fuzzy tracking controller is presented. A new CSO algorithm for the optimization in Fuzzy Logic Controllers (FLC) is presented. The main aim is to use the two bio-inspired algorithms individually to improve of trajectories of an Autonomous Mobile Robot. CSO algorithm shows better results when compared to BCO in the simulation results for this control problem.

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Author information

Authors and Affiliations

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

    Leticia Amador-Angulo & Oscar Castillo

Authors
  1. Leticia Amador-Angulo
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  2. Oscar Castillo
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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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Amador-Angulo, L., Castillo, O. (2021). Optimization of Fuzzy Trajectory Tracking in Autonomous Mobile Robots Based on Bio-inspired Algorithms. 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_15

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