Optimisation of Model Predictive Torque Control Strategy with Standard and Multi-Objective Genetic Algorithms

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dc.authoridZerdali, Emrah/0000-0003-1755-0327
dc.contributor.authorZerdali, Emrah
dc.contributor.authorGurel, Aycan
dc.date.accessioned2024-11-07T13:31:30Z
dc.date.available2024-11-07T13:31:30Z
dc.date.issued2023
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractIn this paper, the flux error-related weighting factor (WF) of the predictive torque control (PTC) strategy for induction motor (IM) control is optimised by a standard genetic algorithm (SGA) through speed errors only and multi-objective genetic algorithm (MOGA) through torque and flux errors. This paper compares the performances of both optimisation methods. Compared to MOGA, SGA offers a straightforward way to select WF and does not need a decision-making method to choose a final solution. But MOGA considers the given problem in a multi-objective way and directly optimises the control objectives of the PTC strate-gy. Comparisons are made over the flux and torque ripples, total harmonic distortion of stator phase current, and average switching frequency for different operating conditions. Simulation results show that both methods choose a close WF value. Consequently, SGA stands out in the optimisation of the PTC strategy with its simple structure.
dc.identifier.doi10.2478/pead-2023-0020
dc.identifier.endpage334
dc.identifier.issn2451-0262
dc.identifier.issn2543-4292
dc.identifier.issue1
dc.identifier.startpage325
dc.identifier.urihttps://doi.org/10.2478/pead-2023-0020
dc.identifier.urihttps://hdl.handle.net/11480/14868
dc.identifier.volume8
dc.identifier.wosWOS:001084856800001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherSciendo
dc.relation.ispartofPower Electronics and Drives
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241106
dc.subjectElectric Drive System
dc.subjectInduction Motor
dc.subjectModel Predictive Control
dc.subjectOptimisation
dc.subjectGenetic Algorithm
dc.titleOptimisation of Model Predictive Torque Control Strategy with Standard and Multi-Objective Genetic Algorithms
dc.typeArticle

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