Neural Network Aided Unscented Kalman Filter for Sensorless Control of PMSM
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F11%3A43898628" target="_blank" >RIV/49777513:23220/11:43898628 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Neural Network Aided Unscented Kalman Filter for Sensorless Control of PMSM
Original language description
This paper introduces neural network aided unscented Kalman filter (NNUKF) for sensorless control of ac motor drives. Unscented Kalman filter (UKF) is completed by on-line trained neural network which compensates unmodeled dynamics and uncertainties of adrive model. This technique significantly improves behaviour of estimator in critical operating states, especially in low speeds.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JA - Electronics and optoelectronics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
EPE 2011 - The 14th European Conference on Power Electronics and Applications
ISBN
978-90-75815-15-3
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
1-9
Publisher name
IEEE
Place of publication
New York
Event location
Birmingham
Event date
Sep 30, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000308003505007