Multiobjective genetic estimation to induction motor parameters

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dc.contributor.authorSag, Tahir
dc.contributor.authorCunkas, Mehmet
dc.date.accessioned2020-03-26T17:17:43Z
dc.date.available2020-03-26T17:17:43Z
dc.date.issued2007
dc.departmentSelçuk Üniversitesien_US
dc.descriptionJoint Conference on Electromotion/IEEE Aegean Conference on Electrical Machines and Power Electronics/ -- SEP 10-12, 2007 -- Bodrum, TURKEYen_US
dc.description.abstractIn order to simplify the offline identification of induction motor parameters, a method based on optimization using a multiobjective genetic algorithm is proposed. The non-dominated sorting genetic algorithm (NSGA-II) is used to minimize the error between the actual data and an estimated model. The robustness of the method is shown by identifying parameters of the induction motor in three different cases. The simulation results show that the method successfully estimates the motor parameters.en_US
dc.description.sponsorshipMiddle East Tech Univ, IEEE, PELS, PESen_US
dc.identifier.endpage631en_US
dc.identifier.isbn978-1-4244-0890-0
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage628en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/21483
dc.identifier.wosWOS:000256943100109en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofINTERNATIONAL AEGEAN CONFERENCE ON ELECTRICAL MACHINES AND POWER ELECTRONICS & ELECTROMOTION, PROCEEDINGSen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectmultiobjective genetic algorithmen_US
dc.subjectinduction motoren_US
dc.subjectparameter estimationen_US
dc.titleMultiobjective genetic estimation to induction motor parametersen_US
dc.typeConference Objecten_US

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