A genetic algorithm optimization of hybrid fuzzy-fuzzy rules in induction motor control

This paper discusses speed control performance of a proposed hybrid fuzzy-fuzzy controller (HFFC) in a variable speed induction motor (IM) drive system. With respect to finding the rule base of the fuzzy controller, a simple genetic algorithm (GA) is employed to resolve the problem of optimization t...

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Main Authors: Magzoub, M., Saad, N., Ibrahim, R., Irfan, M.
Format: Article
Published: Institute of Electrical and Electronics Engineers Inc. 2017
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85012031707&doi=10.1109%2fICIAS.2016.7824078&partnerID=40&md5=354019fed5e8e007a8e674d23d67c4ef
http://eprints.utp.edu.my/20202/
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spelling my.utp.eprints.202022018-04-22T14:45:31Z A genetic algorithm optimization of hybrid fuzzy-fuzzy rules in induction motor control Magzoub, M. Saad, N. Ibrahim, R. Irfan, M. This paper discusses speed control performance of a proposed hybrid fuzzy-fuzzy controller (HFFC) in a variable speed induction motor (IM) drive system. With respect to finding the rule base of the fuzzy controller, a simple genetic algorithm (GA) is employed to resolve the problem of optimization to diminish an objective function, i.e., the Integrated Absolute Error (IAE) criterion. The principle of HFFC is established with the aim of overcoming the shortcoming of the field oriented control (FOC) technique. Simulation results show that HFFC with GA-optimized is the better strategy as compared to HFFC without GA, and conventional hybrid fuzzy-PI controller (HFPIC) for the speed control of IM. © 2016 IEEE. Institute of Electrical and Electronics Engineers Inc. 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85012031707&doi=10.1109%2fICIAS.2016.7824078&partnerID=40&md5=354019fed5e8e007a8e674d23d67c4ef Magzoub, M. and Saad, N. and Ibrahim, R. and Irfan, M. (2017) A genetic algorithm optimization of hybrid fuzzy-fuzzy rules in induction motor control. International Conference on Intelligent and Advanced Systems, ICIAS 2016 . http://eprints.utp.edu.my/20202/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description This paper discusses speed control performance of a proposed hybrid fuzzy-fuzzy controller (HFFC) in a variable speed induction motor (IM) drive system. With respect to finding the rule base of the fuzzy controller, a simple genetic algorithm (GA) is employed to resolve the problem of optimization to diminish an objective function, i.e., the Integrated Absolute Error (IAE) criterion. The principle of HFFC is established with the aim of overcoming the shortcoming of the field oriented control (FOC) technique. Simulation results show that HFFC with GA-optimized is the better strategy as compared to HFFC without GA, and conventional hybrid fuzzy-PI controller (HFPIC) for the speed control of IM. © 2016 IEEE.
format Article
author Magzoub, M.
Saad, N.
Ibrahim, R.
Irfan, M.
spellingShingle Magzoub, M.
Saad, N.
Ibrahim, R.
Irfan, M.
A genetic algorithm optimization of hybrid fuzzy-fuzzy rules in induction motor control
author_facet Magzoub, M.
Saad, N.
Ibrahim, R.
Irfan, M.
author_sort Magzoub, M.
title A genetic algorithm optimization of hybrid fuzzy-fuzzy rules in induction motor control
title_short A genetic algorithm optimization of hybrid fuzzy-fuzzy rules in induction motor control
title_full A genetic algorithm optimization of hybrid fuzzy-fuzzy rules in induction motor control
title_fullStr A genetic algorithm optimization of hybrid fuzzy-fuzzy rules in induction motor control
title_full_unstemmed A genetic algorithm optimization of hybrid fuzzy-fuzzy rules in induction motor control
title_sort genetic algorithm optimization of hybrid fuzzy-fuzzy rules in induction motor control
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2017
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85012031707&doi=10.1109%2fICIAS.2016.7824078&partnerID=40&md5=354019fed5e8e007a8e674d23d67c4ef
http://eprints.utp.edu.my/20202/
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score 13.18916