Publication:
A Quantum Lightning Search Algorithm-Based Fuzzy Speed Controller for Induction Motor Drive

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dc.citedby20
dc.contributor.authorHannan M.A.en_US
dc.contributor.authorAli J.A.en_US
dc.contributor.authorHussain A.en_US
dc.contributor.authorHasim F.H.en_US
dc.contributor.authorAmirulddin U.A.U.en_US
dc.contributor.authorUddin M.N.en_US
dc.contributor.authorBlaabjerg F.en_US
dc.contributor.authorid7103014445en_US
dc.contributor.authorid56540826800en_US
dc.contributor.authorid57208481391en_US
dc.contributor.authorid23094411600en_US
dc.contributor.authorid26422804600en_US
dc.contributor.authorid55663372800en_US
dc.contributor.authorid7004992352en_US
dc.date.accessioned2023-05-29T06:37:33Z
dc.date.available2023-05-29T06:37:33Z
dc.date.issued2017
dc.descriptionElectric drives; Electric inverters; Fuzzy logic; Induction motors; Learning algorithms; Lightning; MATLAB; Membership functions; Optimization; Pulse width modulation; Speed; Speed control; Statistics; Switches; Vector spaces; Voltage control; IM drive; Search Algorithms; Sociology; Space vector pulse width modulation; Speed controller; SVPWM; validation; Controllersen_US
dc.description.abstractThis paper presents a quantum lightning search algorithm (QLSA)-based optimization technique for controlling speed of the induction motor (IM) drive. The developed QLSA is implemented in fuzzy logic controller to generate suitable input and output fuzzy membership function for IM drive speed controller. The main objective of this paper is to develop QLSA-based fuzzy (QLSAF) speed controller to minimise the mean absolute error in order to improve the performance of the IM drive with changes in speed and mechanical load. The QLSAF-based speed controller is implemented in simulation model in the MATLAB/Simulink environment and the prototype is fabricated and experimentally tested in a fully integrated DSP for controlling the IM drive system. The experimental results of the developed QLSAF speed controller are compared with the simulation results under different performance conditions. Several experimental results show that there are good agreement of the controller parameters, SVPWM signals, and different types of speed responses and stator currents with the simulation results, which are verified and validated the performance of the proposed QLSAF speed controller. Also, the proposed QLSAF speed controller outperforms other studies with settling time in simulation and in experimental implementation, which validates the controller performance as well. � 2013 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ACCESS.2017.2778081
dc.identifier.epage1223
dc.identifier.scopus2-s2.0-85037622516
dc.identifier.spage1214
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85037622516&doi=10.1109%2fACCESS.2017.2778081&partnerID=40&md5=b75c593fb4681e31aea5d33f2dee47f1
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23040
dc.identifier.volume6
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofAll Open Access, Gold, Green
dc.sourceScopus
dc.sourcetitleIEEE Access
dc.titleA Quantum Lightning Search Algorithm-Based Fuzzy Speed Controller for Induction Motor Driveen_US
dc.typeArticleen_US
dspace.entity.typePublication
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