A Comparative Study on Adaptive EKF Observers for State and Parameter Estimation of Induction Motor

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dc.authoridZerdali, Emrah/0000-0003-1755-0327
dc.contributor.authorZerdali, Emrah
dc.date.accessioned2024-11-07T13:24:44Z
dc.date.available2024-11-07T13:24:44Z
dc.date.issued2020
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractIn this article, conventional extended Kalman filter (EKF) and adaptive extended Kalman filters (AEKFs) based on adaptive fading, strong tracking, and innovation are compared for state and parameter estimation problem of induction motor (IM) by considering their estimation performances and computational burdens. The estimation performance of EKFs depends on the proper selection of system and measurement noise covariance matrices. However, it is hard to select optimum elements of those matrices using the trial-and-error method, and those are affected by the operating conditions of IM. Therefore, different AEKF approaches with the ability to update those matrices online according to the operating conditions have been proposed in the literature. However, to the best of the author's knowledge, no comparison has been yet reported as to which observer is more effective for real-time state and parameter estimation problem of IM. This paper focuses on the detailed comparison of those observers and provides useful results to the literature.
dc.identifier.doi10.1109/TEC.2020.2979850
dc.identifier.endpage1452
dc.identifier.issn0885-8969
dc.identifier.issn1558-0059
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85081584373
dc.identifier.scopusqualityQ1
dc.identifier.startpage1443
dc.identifier.urihttps://doi.org/10.1109/TEC.2020.2979850
dc.identifier.urihttps://hdl.handle.net/11480/14277
dc.identifier.volume35
dc.identifier.wosWOS:000562429600029
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIEEE-Inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Transactions on Energy Conversion
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectObservers
dc.subjectCovariance matrices
dc.subjectKalman filters
dc.subjectFading channels
dc.subjectNoise measurement
dc.subjectStators
dc.subjectAdaptive extended Kalman filter (AEKFs)
dc.subjectinduction motor
dc.subjectspeed-sensorless control
dc.subjectparameter estimation
dc.subjectstate estimation
dc.titleA Comparative Study on Adaptive EKF Observers for State and Parameter Estimation of Induction Motor
dc.typeArticle

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