FPGA implementation of marginalized particle filter for sensorless control of PMSM drives

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F13%3A43919611" target="_blank" >RIV/49777513:23220/13:43919611 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6700510&queryText%3DFPGA+implementation+of+marginalized+particle+filter+for+sensorless+control+of+PMSM+drives" target="_blank" >http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6700510&queryText%3DFPGA+implementation+of+marginalized+particle+filter+for+sensorless+control+of+PMSM+drives</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IECON.2013.6700510" target="_blank" >10.1109/IECON.2013.6700510</a>

Jazyk výsledku

angličtina

Název v původním jazyce

FPGA implementation of marginalized particle filter for sensorless control of PMSM drives

Popis výsledku v původním jazyce

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. In effect, this allows to represent accurately the inherent non-Gaussianity and nonlinearity of the model. This allows estimation of the rotor position of the PMSM drive in the full speed range, including the standstill. The main disadvantage is its high computationalcost. In this paper, we present an implementation of the marginalized particle filter in the field programmable logic array (FPGA). The parallel nature of the MPF algorithm allows to use pipelining which yields speedup in the order of magnitude in comparison to the DSP implementatio n. The sensorless control of the drive is implemented on a board with both DSP and FPGA, where the drive control runs on the DSP and the MPF estimator in the FPGA. Execution time of the estimator is thus neg

Název v anglickém jazyce

FPGA implementation of marginalized particle filter for sensorless control of PMSM drives

Popis výsledku anglicky

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. In effect, this allows to represent accurately the inherent non-Gaussianity and nonlinearity of the model. This allows estimation of the rotor position of the PMSM drive in the full speed range, including the standstill. The main disadvantage is its high computationalcost. In this paper, we present an implementation of the marginalized particle filter in the field programmable logic array (FPGA). The parallel nature of the MPF algorithm allows to use pipelining which yields speedup in the order of magnitude in comparison to the DSP implementatio n. The sensorless control of the drive is implemented on a board with both DSP and FPGA, where the drive control runs on the DSP and the MPF estimator in the FPGA. Execution time of the estimator is thus neg

Druh

D - Stať ve sborníku

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society

ISBN

978-1-4799-0224-8

ISSN

1553-572X

e-ISSN

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Počet stran výsledku

6

Strana od-do

8227-8232

Název nakladatele

IEEE

Místo vydání

Vienna

Místo konání akce

Vienna

Datum konání akce

10. 11. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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