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Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement

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dc.citedby18
dc.contributor.authorHannan M.A.en_US
dc.contributor.authorAli J.A.en_US
dc.contributor.authorHossain Lipu M.S.en_US
dc.contributor.authorMohamed A.en_US
dc.contributor.authorKer P.J.en_US
dc.contributor.authorIndra Mahlia T.M.en_US
dc.contributor.authorMansor M.en_US
dc.contributor.authorHussain A.en_US
dc.contributor.authorMuttaqi K.M.en_US
dc.contributor.authorDong Z.Y.en_US
dc.contributor.authorid7103014445en_US
dc.contributor.authorid56540826800en_US
dc.contributor.authorid36518949700en_US
dc.contributor.authorid57195440511en_US
dc.contributor.authorid37461740800en_US
dc.contributor.authorid56997615100en_US
dc.contributor.authorid6701749037en_US
dc.contributor.authorid57208481391en_US
dc.contributor.authorid55582332500en_US
dc.contributor.authorid56608244300en_US
dc.date.accessioned2023-05-29T08:06:55Z
dc.date.available2023-05-29T08:06:55Z
dc.date.issued2020
dc.descriptionaccuracy assessment; algorithm; control system; experimental study; instrumentation; optimization; performance assessment; simulation; algorithm; article; fuzzy logic; lightning; motor performance; simulation; velocityen_US
dc.description.abstractThree-phase induction motors (TIMs) are widely used for machines in industrial operations. As an accurate and robust controller, fuzzy logic controller (FLC) is crucial in designing TIMs control systems. The performance of FLC highly depends on the membership function (MF) variables, which are evaluated by heuristic approaches, leading to a high processing time. To address these issues, optimisation algorithms for TIMs have received increasing interest among researchers and industrialists. Here, we present an advanced and efficient quantum-inspired lightning search algorithm (QLSA) to avoid exhaustive conventional heuristic procedures when obtaining MFs. The accuracy of the QLSA based FLC (QLSAF) speed control is superior to other controllers in terms of transient response, damping capability and minimisation of statistical errors under diverse speeds and loads. The performance of the proposed QLSAF speed controller is validated through experiments. Test results under different conditions show consistent speed responses and stator currents with the simulation results. � 2020, The Author(s).en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo3792
dc.identifier.doi10.1038/s41467-020-17623-5
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85088779717
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85088779717&doi=10.1038%2fs41467-020-17623-5&partnerID=40&md5=4e4a551c53757ca165724a7f68e8bb21
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25138
dc.identifier.volume11
dc.publisherNature Researchen_US
dc.relation.ispartofAll Open Access, Gold, Green
dc.sourceScopus
dc.sourcetitleNature Communications
dc.titleRole of optimization algorithms based fuzzy controller in achieving induction motor performance enhancementen_US
dc.typeArticleen_US
dspace.entity.typePublication
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