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Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control

Interval Type-2 Fuzzy Logic Control (IT2FLC) possesses a high control ability in a way that it can optimally handle the presence of uncertainty in a system dynamic. However, the design of such a control scheme is a challenging task due to its complex structure and nonlinear behavior. A Manta Ray For...

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Main Authors: Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir, Nor Maniha, Abdul Ghani, Mohammad Osman, Tokhi
Format: Article
Language:English
Published: SAGE Publications Inc. 2024
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/41331/1/Opposition-based%20manta%20ray%20foraging%20algorithm%20for%20global%20optimization.pdf
http://umpir.ump.edu.my/id/eprint/41331/
https://doi.org/10.1177/14613484241242737
https://doi.org/10.1177/14613484241242737
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spelling my.ump.umpir.413312024-07-01T01:08:51Z http://umpir.ump.edu.my/id/eprint/41331/ Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control Ahmad Azwan, Abdul Razak Ahmad Nor Kasruddin, Nasir Nor Maniha, Abdul Ghani Mohammad Osman, Tokhi T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Interval Type-2 Fuzzy Logic Control (IT2FLC) possesses a high control ability in a way that it can optimally handle the presence of uncertainty in a system dynamic. However, the design of such a control scheme is a challenging task due to its complex structure and nonlinear behavior. A Manta Ray Foraging Optimization (MRFO) is a promising algorithm that can be applied to optimize the control design. However, MRFO still suffers the local optima problem due to unbalance exploration-exploitation of the MRFO agents and hence limiting the performance of the desired control. In this paper, Standard, Quasi, Super, and Quasi-Reflected opposition strategies are integrated into the MRFO structure. Each strategy enhances the exploration-exploitation capability and offers different approaches of varying agent’s step size relative to the algorithm’s iteration. The proposed opposition-based MRFO (OMRFO) algorithms are applied to optimize the IT2FLC control design for a laboratory-scaled inverted pendulum system. Moreover, as the algorithms are also promising strategies to other problems, they are applied to solve 50D of 30 IEEE CEC14 benchmark functions representing problems with different features. Performance analysis of the algorithms is statistically conducted using Wilcoxon sign rank and Friedman tests. The result shows that the performance of MRFO and Quasi-Reflected-OMRFO are equal, while all other OMRFO variants show a significant improvement and better rank over the MRFO. The Super and Quasi OMRFO-IT2FLC schemes acquired the best responses for the cart and pendulum, respectively. SAGE Publications Inc. 2024-04-01 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/41331/1/Opposition-based%20manta%20ray%20foraging%20algorithm%20for%20global%20optimization.pdf Ahmad Azwan, Abdul Razak and Ahmad Nor Kasruddin, Nasir and Nor Maniha, Abdul Ghani and Mohammad Osman, Tokhi (2024) Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control. Journal of Low Frequency Noise Vibration and Active Control. pp. 1-24. ISSN 1461-3484. (Published) https://doi.org/10.1177/14613484241242737 https://doi.org/10.1177/14613484241242737
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Ahmad Azwan, Abdul Razak
Ahmad Nor Kasruddin, Nasir
Nor Maniha, Abdul Ghani
Mohammad Osman, Tokhi
Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control
description Interval Type-2 Fuzzy Logic Control (IT2FLC) possesses a high control ability in a way that it can optimally handle the presence of uncertainty in a system dynamic. However, the design of such a control scheme is a challenging task due to its complex structure and nonlinear behavior. A Manta Ray Foraging Optimization (MRFO) is a promising algorithm that can be applied to optimize the control design. However, MRFO still suffers the local optima problem due to unbalance exploration-exploitation of the MRFO agents and hence limiting the performance of the desired control. In this paper, Standard, Quasi, Super, and Quasi-Reflected opposition strategies are integrated into the MRFO structure. Each strategy enhances the exploration-exploitation capability and offers different approaches of varying agent’s step size relative to the algorithm’s iteration. The proposed opposition-based MRFO (OMRFO) algorithms are applied to optimize the IT2FLC control design for a laboratory-scaled inverted pendulum system. Moreover, as the algorithms are also promising strategies to other problems, they are applied to solve 50D of 30 IEEE CEC14 benchmark functions representing problems with different features. Performance analysis of the algorithms is statistically conducted using Wilcoxon sign rank and Friedman tests. The result shows that the performance of MRFO and Quasi-Reflected-OMRFO are equal, while all other OMRFO variants show a significant improvement and better rank over the MRFO. The Super and Quasi OMRFO-IT2FLC schemes acquired the best responses for the cart and pendulum, respectively.
format Article
author Ahmad Azwan, Abdul Razak
Ahmad Nor Kasruddin, Nasir
Nor Maniha, Abdul Ghani
Mohammad Osman, Tokhi
author_facet Ahmad Azwan, Abdul Razak
Ahmad Nor Kasruddin, Nasir
Nor Maniha, Abdul Ghani
Mohammad Osman, Tokhi
author_sort Ahmad Azwan, Abdul Razak
title Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control
title_short Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control
title_full Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control
title_fullStr Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control
title_full_unstemmed Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control
title_sort opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control
publisher SAGE Publications Inc.
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/41331/1/Opposition-based%20manta%20ray%20foraging%20algorithm%20for%20global%20optimization.pdf
http://umpir.ump.edu.my/id/eprint/41331/
https://doi.org/10.1177/14613484241242737
https://doi.org/10.1177/14613484241242737
_version_ 1822924424702066688
score 13.232414

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