Strong Tracking Extended Kalman Filter Based Speed and Load Torque Estimations of Induction Motor

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dc.authoridZerdali, Emrah/0000-0003-1755-0327
dc.contributor.authorZerdali, Emrah
dc.date.accessioned2024-11-07T13:23:54Z
dc.date.available2024-11-07T13:23:54Z
dc.date.issued2019
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description1st Global Power, Energy and Communication Conference (IEEE GPECOM) -- JUN 12-15, 2019 -- Nevsehir, TURKEY
dc.description.abstractIn this paper, a strong tracking extended Kalman filter (STEKF) algorithm estimating the stator stationary axis components of stator currents and rotor fluxes, rotor mechanical speed, and load torque is proposed for speed-sensorless control applications of induction motor. As known, Kalman filtering requires complete specifications of both dynamical and statistical model parameters of a system to achieve optimal performance. Therefore, the proper determination of system and measurement noise covariance matrices is crucial. However, these matrices are generally assumed as constant and determined by trial-and-error method. Failure to find optimum values by trial-and-error method for all operating conditions and the variation of these matrices according to operating conditions cause the divergence of algorithm or deterioration of its performance. Therefore, a sixth-order STEKF algorithm improving the estimation performance is designed and tested in simulations. Moreover, its performance is compared to that of standard EKF in order to prove its superiority.
dc.description.sponsorshipNevsehir Haci Bektas Veli Univ,IEEE,IEEE Reg 8,IEEE Turkey Sect,IEEE Ind Applicat Soc,IEEE Ind Elect Soc,IEEE Power & Energy Soc,Aalborg Univ,Univ Nova Lisboa,Gazi Univ
dc.identifier.endpage221
dc.identifier.isbn978-1-5386-8086-5
dc.identifier.scopus2-s2.0-85070656684
dc.identifier.scopusqualityN/A
dc.identifier.startpage216
dc.identifier.urihttps://hdl.handle.net/11480/13777
dc.identifier.wosWOS:000851517900040
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2019 Ieee 1st Global Power, Energy and Communication Conference (Gpecom2019)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectInduction motor
dc.subjectSpeed-sensorless control
dc.subjectState estimation
dc.subjectStrong tracking extended Kalman filter
dc.titleStrong Tracking Extended Kalman Filter Based Speed and Load Torque Estimations of Induction Motor
dc.typeConference Object

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