About: Marginalized Particle Filter for Sensorless Control of PMSM Drives

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Marginalized particle filter is a stochastic filter combining Kalman filters with particle filters. It decomposes the model into linear and nonlinear part and applies the Kalman filter for the former and the particle filter for the latter. Its application in sensorless control of permanent magnet synchronous motor (PMSM) drives is based on separate treatment of the state variables: the rotor position is represented by a set of samples (particles), and the rotor speed is estimated by the Kalman filters associated with each sample. In effect, this allows to represent accurately the inherent non-Gaussianity and nonlinearity of the model. We show that the resulting filter is capable to estimate the rotor position in the full speed range, including the standstill. Analysis of the filter performance is presented on open-loop off-line analysis of data recorded on a drive prototype. Execution time of optimized implementation of the algorithm for six particles in DSP is comparable to that of the Extended Kalman filter for full state-space model. Closed-loop performance of the filter (a sensorless drive control) is evaluated on developed drive prototype of rated power of 10.7kW. Marginalized particle filter is a stochastic filter combining Kalman filters with particle filters. It decomposes the model into linear and nonlinear part and applies the Kalman filter for the former and the particle filter for the latter. Its application in sensorless control of permanent magnet synchronous motor (PMSM) drives is based on separate treatment of the state variables: the rotor position is represented by a set of samples (particles), and the rotor speed is estimated by the Kalman filters associated with each sample. In effect, this allows to represent accurately the inherent non-Gaussianity and nonlinearity of the model. We show that the resulting filter is capable to estimate the rotor position in the full speed range, including the standstill. Analysis of the filter performance is presented on open-loop off-line analysis of data recorded on a drive prototype. Execution time of optimized implementation of the algorithm for six particles in DSP is comparable to that of the Extended Kalman filter for full state-space model. Closed-loop performance of the filter (a sensorless drive control) is evaluated on developed drive prototype of rated power of 10.7kW. (en)
Title	Marginalized Particle Filter for Sensorless Control of PMSM Drives Marginalized Particle Filter for Sensorless Control of PMSM Drives (en)
skos:prefLabel	Marginalized Particle Filter for Sensorless Control of PMSM Drives Marginalized Particle Filter for Sensorless Control of PMSM Drives (en)
skos:notation	RIV/67985556:_____/12:00383715!RIV13-AV0-67985556
http://linked.open...avai/riv/aktivita	I P
http://linked.open...avai/riv/aktivity	I, P(GAP102/11/0437)
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Šmídl, Václav
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav teorie informace a automatizace AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	148467
http://linked.open...ai/riv/idVysledku	RIV/67985556:_____/12:00383715
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	particle filter; PMSM drive; sensorless control (en)
http://linked.open.../riv/klicoveSlovo	sensorless control particle filter PMSM drive
http://linked.open...ontrolniKodProRIV	[D9D730B1F57C]
http://linked.open...v/mistoKonaniAkce	Montreal
http://linked.open...i/riv/mistoVydani	Montral
http://linked.open...i/riv/nazevZdroje	Proceedings of the 38th Annual Conference of the IEEE Industrial Electronics Society
http://linked.open...in/vavai/riv/obor	JA
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Control and Parameter Identification of AC Electric Drives under Critical Operating Conditions
http://linked.open...UplatneniVysledku	2012
http://linked.open...iv/tvurceVysledku	Šmídl, Václav Peroutka, Z.
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2012-10-25 (xsd:date)
number of pages	6 (xsd:int)
http://purl.org/ne...btex#hasPublisher	IEEE Industrial Electronics Society
https://schema.org/isbn	978-1-4673-2419-9

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