Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive

Fuzzy logic; Induction motors; Learning algorithms; Mean square error; Membership functions; Optimization; Particle swarm optimization (PSO); Rotors; Speed; Speed control; Stators; Torque; Transient analysis; Vector control (Electric machinery); Voltage control; Water craft; Backtracking search algo...

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Main Authors: Hannan M.A., Ali J.A., Mohamed A., Amirulddin U.A.U., Tan N.M.L., Uddin M.N.
Other Authors: 7103014445
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-237882023-05-29T14:51:50Z Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive Hannan M.A. Ali J.A. Mohamed A. Amirulddin U.A.U. Tan N.M.L. Uddin M.N. 7103014445 56540826800 57195440511 26422804600 24537965000 55663372800 Fuzzy logic; Induction motors; Learning algorithms; Mean square error; Membership functions; Optimization; Particle swarm optimization (PSO); Rotors; Speed; Speed control; Stators; Torque; Transient analysis; Vector control (Electric machinery); Voltage control; Water craft; Backtracking search algorithms; Fuzzy membership function; Gravitational search algorithm (GSA); Indirect field oriented control; PI Controller; QLSA; Speed controller; Three phase induction motor; Controllers The main objective of this study is to develop a quantum-behaved lightening search algorithm (QLSA) to improve the indirect field-oriented fuzzy-proportional-integral (PI) controller technique to control a three-phase induction motor (TIM) drive. The generated adaptive PI current control parameters and fuzzy membership functions are carried to design induction motor drive speed controller to minimize the fitness function formulated by QLSA. An optimal QLSA-based indirect field-oriented control (QLSA-IFOC) fitness function is used to reduce the mean absolute error of the rotor speed to improve the performance of the TIM with varying speed and mechanical load. Results obtained from the QLSA-IFOC are compared with those obtained through lightening search algorithm, gravitational search algorithm, backtracking search algorithm, and particle swarm optimization to validate the developed controller. The optimization results of objective functions in terms of box plots and iterations show that the QLSA algorithm outperforms the other optimization algorithms. Moreover, the QLSA-IFOC controller performed well in all tests in terms of transient response. The developed controller also minimizes overshoot, increases damping capability, and reduces the root-mean-square error, as well as standard deviation under sudden change of speed and mechanical loads. A comparative analysis is performed between simulation and experimental results to justify the efficiency of the developed controller. � 1972-2012 IEEE. Final 2023-05-29T06:51:50Z 2023-05-29T06:51:50Z 2018 Conference Paper 10.1109/TIA.2018.2821644 2-s2.0-85044737049 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044737049&doi=10.1109%2fTIA.2018.2821644&partnerID=40&md5=ab1007419047b2adc4e897a4b8f7ee0a https://irepository.uniten.edu.my/handle/123456789/23788 54 4 3793 3805 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Fuzzy logic; Induction motors; Learning algorithms; Mean square error; Membership functions; Optimization; Particle swarm optimization (PSO); Rotors; Speed; Speed control; Stators; Torque; Transient analysis; Vector control (Electric machinery); Voltage control; Water craft; Backtracking search algorithms; Fuzzy membership function; Gravitational search algorithm (GSA); Indirect field oriented control; PI Controller; QLSA; Speed controller; Three phase induction motor; Controllers
author2 7103014445
author_facet 7103014445
Hannan M.A.
Ali J.A.
Mohamed A.
Amirulddin U.A.U.
Tan N.M.L.
Uddin M.N.
format Conference Paper
author Hannan M.A.
Ali J.A.
Mohamed A.
Amirulddin U.A.U.
Tan N.M.L.
Uddin M.N.
spellingShingle Hannan M.A.
Ali J.A.
Mohamed A.
Amirulddin U.A.U.
Tan N.M.L.
Uddin M.N.
Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive
author_sort Hannan M.A.
title Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive
title_short Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive
title_full Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive
title_fullStr Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive
title_full_unstemmed Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive
title_sort quantum-behaved lightning search algorithm to improve indirect field-oriented fuzzy-pi control for im drive
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806425546966433792
score 13.188404