Fuzzy based parameter tuning of EKF observers for sensorless control of induction motors

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dc.contributor.authorAydın, Menekşe
dc.contributor.authorGökaşan, Metin
dc.contributor.authorBogosyan, Seta
dc.date.accessioned2024-06-13T20:18:41Z
dc.date.available2024-06-13T20:18:41Z
dc.date.issued2014
dc.departmentMeslek Yüksekokulu, Gedik Meslek Yüksekokulu, Mekatronik Programı
dc.descriptionIEEE International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) -- 18-20 June, 2014 -- Italy
dc.description.abstractThis study presents a parameter tuning approach for Extended Kalman Filter (EKF) based observers for the sensorless control of Induction Motor (IM) drives. After an analysis performed on the effect of covariance matrix elements of EKF, the study demonstrates the improved performance of the EKF based estimation (performed for stator currents, rotor flux, rotor speed, stator resistance and load torque), via the developed online parameter tuning approach for different speed and load references. Firstly, it has been demonstrated experimentally that covariance matrices used in EKF algorithm vary with the operation conditions. It has specifically been demonstrated that, among the elements of model covariance matrix, the ones corresponding to the rotor flux components are the most effective in correcting the estimations of the related EKF algorithm. To address this issue, an online fuzzy approach is developed based on different load and speed references, of which the inputs are the estimated speed and estimated load torque, and the output consists of the elements of the model covariance matrix related to the rotor flux. The performance of the proposed Fuzzy EKF has been experimentally tested and the results have demonstrated that the proposed scheme can eliminate biases and yields higher estimation accuracy when compared with the standard EKF where the tuning parameters are fixed to constant values.
dc.description.sponsorshipIEEE
dc.identifier.doi10.1109/SPEEDAM.2014.6871980
dc.identifier.endpage1179
dc.identifier.isbn9781479947492
dc.identifier.scopus2-s2.0-84906691668
dc.identifier.scopusqualityN/A
dc.identifier.startpage1174
dc.identifier.urihttps://hdl.handle.net/11501/1492
dc.identifier.urihttps://doi.org/10.1109/SPEEDAM.2014.6871980
dc.identifier.wosWOS:000346502700200
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorAydın, Menekşe
dc.institutionauthorid0000-0002-7434-0994
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartofIEEE International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectAC Motors
dc.subjectFuzzy Logic
dc.subjectExtended Kalman Filters
dc.subjectObservers
dc.titleFuzzy based parameter tuning of EKF observers for sensorless control of induction motors
dc.typeConference Object

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