Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement
accuracy assessment; algorithm; control system; experimental study; instrumentation; optimization; performance assessment; simulation; algorithm; article; fuzzy logic; lightning; motor performance; simulation; velocity
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2023
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my.uniten.dspace-251382023-05-29T16:06:55Z Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement Hannan M.A. Ali J.A. Hossain Lipu M.S. Mohamed A. Ker P.J. Indra Mahlia T.M. Mansor M. Hussain A. Muttaqi K.M. Dong Z.Y. 7103014445 56540826800 36518949700 57195440511 37461740800 56997615100 6701749037 57208481391 55582332500 56608244300 accuracy assessment; algorithm; control system; experimental study; instrumentation; optimization; performance assessment; simulation; algorithm; article; fuzzy logic; lightning; motor performance; simulation; velocity Three-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). Final 2023-05-29T08:06:55Z 2023-05-29T08:06:55Z 2020 Article 10.1038/s41467-020-17623-5 2-s2.0-85088779717 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088779717&doi=10.1038%2fs41467-020-17623-5&partnerID=40&md5=4e4a551c53757ca165724a7f68e8bb21 https://irepository.uniten.edu.my/handle/123456789/25138 11 1 3792 All Open Access, Gold, Green Nature Research Scopus |
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accuracy assessment; algorithm; control system; experimental study; instrumentation; optimization; performance assessment; simulation; algorithm; article; fuzzy logic; lightning; motor performance; simulation; velocity |
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7103014445 |
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7103014445 Hannan M.A. Ali J.A. Hossain Lipu M.S. Mohamed A. Ker P.J. Indra Mahlia T.M. Mansor M. Hussain A. Muttaqi K.M. Dong Z.Y. |
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Article |
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Hannan M.A. Ali J.A. Hossain Lipu M.S. Mohamed A. Ker P.J. Indra Mahlia T.M. Mansor M. Hussain A. Muttaqi K.M. Dong Z.Y. |
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Hannan M.A. Ali J.A. Hossain Lipu M.S. Mohamed A. Ker P.J. Indra Mahlia T.M. Mansor M. Hussain A. Muttaqi K.M. Dong Z.Y. Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement |
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Hannan M.A. |
title |
Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement |
title_short |
Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement |
title_full |
Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement |
title_fullStr |
Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement |
title_full_unstemmed |
Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement |
title_sort |
role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement |
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Nature Research |
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2023 |
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1806423426065235968 |