FPGA implementation of Rao-Blackwellized particle filter and its application to sensorless drive control

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F14%3A43922641" target="_blank" >RIV/49777513:23220/14:43922641 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985556:_____/14:00431968

Výsledek na webu

<a href="http://10.3182/20140824-6-ZA-1003.01557" target="_blank" >http://10.3182/20140824-6-ZA-1003.01557</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3182/20140824-6-ZA-1003.01557" target="_blank" >10.3182/20140824-6-ZA-1003.01557</a>

Jazyk výsledku

angličtina

Název v původním jazyce

FPGA implementation of Rao-Blackwellized particle filter and its application to sensorless drive control

Popis výsledku v původním jazyce

Rao-Blackwellied particle filter is a stochastic filter combining Kalman filters with particle filters. It is suitable for models that could be decomposed into linear and nonlinear part. Since the conditionally linear part can be solved by the Kalman filter, the sequential Monte Carlo is run only on the non-linear subspace. The resulting algorithm is a parallel evaluation of multiple Kalman filters with resampling. The parallel nature of this algorithm allows for very efficient implementation in hardware supporting parallel computation processes. In this contribution, we present implementation of the algorithm in the Field Programmable Gate Array (FPGA). Due to the used model and optimized implementation, the execution time of the filter is in units ofmicroseconds and scales very favorably with the number of particles. This is demonstrated experimentally on a laboratory prototype of sensorless drive with permanent magnet synchronous machine (PMSM) of rated power of 10.7kW.

Název v anglickém jazyce

FPGA implementation of Rao-Blackwellized particle filter and its application to sensorless drive control

Popis výsledku anglicky

Rao-Blackwellied particle filter is a stochastic filter combining Kalman filters with particle filters. It is suitable for models that could be decomposed into linear and nonlinear part. Since the conditionally linear part can be solved by the Kalman filter, the sequential Monte Carlo is run only on the non-linear subspace. The resulting algorithm is a parallel evaluation of multiple Kalman filters with resampling. The parallel nature of this algorithm allows for very efficient implementation in hardware supporting parallel computation processes. In this contribution, we present implementation of the algorithm in the Field Programmable Gate Array (FPGA). Due to the used model and optimized implementation, the execution time of the filter is in units ofmicroseconds and scales very favorably with the number of particles. This is demonstrated experimentally on a laboratory prototype of sensorless drive with permanent magnet synchronous machine (PMSM) of rated power of 10.7kW.

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

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 19th IFAC World Congress, 2014

ISBN

978-3-902823-62-5

ISSN

1474-6670

e-ISSN

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Počet stran výsledku

6

Strana od-do

8669-8674

Název nakladatele

Elsevier

Místo vydání

Amsterdam

Místo konání akce

Cape Town

Datum konání akce

24. 8. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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