research-article

Type-1 and Type-2 fuzzy logic controller design using a Hybrid PSO-GA optimization method

Authors:

Ricardo Martínez-Soto,

Oscar Castillo,

Luis T. AguilarAuthors Info & Claims

Information Sciences—Informatics and Computer Science, Intelligent Systems, Applications: An International Journal, Volume 285, Issue C

Pages 35 - 49

https://doi.org/10.1016/j.ins.2014.07.012

Published: 20 November 2014 Publication History

Abstract

In this paper we propose a Hybrid PSO-GA optimization method for automatic design of fuzzy logic controllers (FLC) to minimize the steady state error of a plant's response. We test the optimal FLC obtained by the Hybrid PSO-GA method using benchmark control plants and an autonomous mobile robot for trajectory tracking control. The bio-inspired method is used to find the parameters of the membership functions of the FLC to obtain the optimal controller for the respective plants. Simulation results show the feasibility of the proposed approach for these control applications. A comparison is also made among the proposed Hybrid PSO-GA, with GA and PSO to determine if there is a significant difference in the results.

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Cited By

Namadchian ZZare A(2021)Stability analysis of dynamic interval type‐2 fuzzy control systems in frequency domainAsian Journal of Control10.1002/asjc.240723:6(2729-2739)Online publication date: 1-Nov-2021
https://dl.acm.org/doi/10.1002/asjc.2407
Namadchian ZZare A(2020)Stability analysis of dynamic nonlinear interval type-2 TSK fuzzy control systems based on describing functionSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-020-04811-024:19(14623-14636)Online publication date: 7-Mar-2020
https://dl.acm.org/doi/10.1007/s00500-020-04811-0
Mahmoodabadi MZiaei A(2019)Inverse Dynamics Based Optimal Fuzzy Controller for a Robot Manipulator via Particle Swarm OptimizationJournal of Robotics10.1155/2019/50521852019Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1155/2019/5052185
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Type-1 and Type-2 fuzzy logic controller design using a Hybrid PSO-GA optimization method
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
    2. Search methodologies

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cover image Information Sciences: an International Journal

Information Sciences: an International Journal Volume 285, Issue C

November 2014

237 pages

ISSN:0020-0255

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Copyright © Elsevier Inc.

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Elsevier Science Inc.

United States

Publication History

Published: 20 November 2014

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Cited By

Namadchian ZZare A(2021)Stability analysis of dynamic interval type‐2 fuzzy control systems in frequency domainAsian Journal of Control10.1002/asjc.240723:6(2729-2739)Online publication date: 1-Nov-2021
https://dl.acm.org/doi/10.1002/asjc.2407
Namadchian ZZare A(2020)Stability analysis of dynamic nonlinear interval type-2 TSK fuzzy control systems based on describing functionSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-020-04811-024:19(14623-14636)Online publication date: 7-Mar-2020
https://dl.acm.org/doi/10.1007/s00500-020-04811-0
Mahmoodabadi MZiaei A(2019)Inverse Dynamics Based Optimal Fuzzy Controller for a Robot Manipulator via Particle Swarm OptimizationJournal of Robotics10.1155/2019/50521852019Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1155/2019/5052185
Lee CWang MWang CTeytaud OLiu JLin SHung P(2018)PSO-Based Fuzzy Markup Language for Student Learning Performance Evaluation and Educational ApplicationIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2018.281081426:5(2618-2633)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1109/TFUZZ.2018.2810814
Hamza MYap HChoudhury IChiroma HKumbasar T(2018)A survey on advancement of hybrid type 2 fuzzy sliding mode controlNeural Computing and Applications10.1007/s00521-017-3144-z30:2(331-353)Online publication date: 1-Jul-2018
https://dl.acm.org/doi/10.1007/s00521-017-3144-z
Antão RMota AMartins R(2018)Model-based control using interval type-2 fuzzy logic systemsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-016-2358-922:2(607-620)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1007/s00500-016-2358-9
Hamza MYap HChoudhury I(2017)Recent advances on the use of meta-heuristic optimization algorithms to optimize the type-2 fuzzy logic systems in intelligent controlNeural Computing and Applications10.1007/s00521-015-2111-928:5(979-999)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1007/s00521-015-2111-9
Lin CGuo KLin Y(2016)A simple and effective remedial learning system with a fuzzy expert systemJournal of Computer Assisted Learning10.1111/jcal.1216032:6(647-662)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1111/jcal.12160
Zhou MDong HWang FWang QYang X(2016)Modeling and simulation of pedestrian dynamical behavior based on a fuzzy logic approachInformation Sciences: an International Journal10.1016/j.ins.2016.04.018360:C(112-130)Online publication date: 10-Sep-2016
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Meng ALi ZYin HChen SGuo Z(2016)Accelerating particle swarm optimization using crisscross searchInformation Sciences: an International Journal10.1016/j.ins.2015.08.018329:C(52-72)Online publication date: 1-Feb-2016
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