Comparative study of an EKF-based parameter estimation and a nonlinear optimization-based estimation on PMSM system identification

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buir.contributor.authorSel, Bilgehan
buir.contributor.orcidSel, Bilgehan|0000-0001-8701-6539
dc.citation.epage14en_US
dc.citation.issueNumber19en_US
dc.citation.spage1en_US
dc.citation.volumeNumber14en_US
dc.contributor.authorSel, Artun
dc.contributor.authorSel, Bilgehan
dc.contributor.authorCoskun, Umit
dc.contributor.authorKasnakoğlu, Cosku
dc.date.accessioned2022-02-18T13:00:49Z
dc.date.available2022-02-18T13:00:49Z
dc.date.issued2021-09-25
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractIn this study, two different parameter estimation algorithms are studied and compared. Iterated EKF and a nonlinear optimization algorithm based on on-line search methods are imple mented to estimate parameters of a given permanent magnet synchronous motor whose dynamics are assumed to be known and nonlinear. In addition to parameters, initial conditions of the dynami cal system are also considered to be unknown, and that comprises one of the differences of those two algorithms. The implementation of those algorithms for the problem and adaptations of the methods are detailed for some other variations of the problem that are reported in the literature. As for the computational aspect of the study, a convexity study is conducted to obtain the spherical neighborhood of the unknown terms around their correct values in the space. To obtain such a range is important to determine convexity properties of the optimization problem given in the estimation problem. In this study, an EKF-based parameter estimation algorithm and an optimization-based method are designed for a given nonlinear dynamical system. The design steps are detailed, and the efficacies and shortcomings of both algorithms are discussed regarding the numerical simulations.en_US
dc.description.provenanceSubmitted by Türkan Cesur (cturkan@bilkent.edu.tr) on 2022-02-18T13:00:49Z No. of bitstreams: 1 Comparative_Study_of_an_EKF-Based_Parameter_Estimation_and_a_Nonlinear_Optimization-Based_Estimation_on_PMSM_System_Identification.pdf: 2240830 bytes, checksum: 2b45c405f305c9acd044ea906cb2d2a6 (MD5)en
dc.description.provenanceMade available in DSpace on 2022-02-18T13:00:49Z (GMT). No. of bitstreams: 1 Comparative_Study_of_an_EKF-Based_Parameter_Estimation_and_a_Nonlinear_Optimization-Based_Estimation_on_PMSM_System_Identification.pdf: 2240830 bytes, checksum: 2b45c405f305c9acd044ea906cb2d2a6 (MD5) Previous issue date: 2021-09-25en
dc.identifier.doi10.3390/en14196108en_US
dc.identifier.eissn1996-1073
dc.identifier.urihttp://hdl.handle.net/11693/77518
dc.language.isoEnglishen_US
dc.publisherMDPI AGen_US
dc.relation.isversionofhttps://doi.org/10.3390/en14196108en_US
dc.source.titleEnergiesen_US
dc.subjectEKFen_US
dc.subjectNonlinear optimizationen_US
dc.subjectParameter estimationen_US
dc.subjectState estimationen_US
dc.subjectSystem identificationen_US
dc.titleComparative study of an EKF-based parameter estimation and a nonlinear optimization-based estimation on PMSM system identificationen_US
dc.typeArticleen_US

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