State Estimation of Induction Motor Drives Using the Unscented Kalman Filter

Cristian Lascu, Saeed Jafarzadeh, M.Sami Fadali

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

115 Citationer (Scopus)

Resumé

This paper investigates the application, design, and
implementation of unscented Kalman filters (KFs) (UKFs) for
induction motor (IM) sensorless drives. UKFs use nonlinear unscented
transforms (UTs) in the prediction step in order to preserve
the stochastic characteristics of a nonlinear system. The
advantage of using UTs is their ability to capture the nonlinear
behavior of the system, unlike extended KFs (EKFs) that use
linearized models. Four original variants of the UKF for IM
state estimation, based on different UTs, are described, analyzed,
and compared. The four transforms are basic, general, simplex,
and spherical UTs. This paper discusses the theoretical aspects and
implementation details of the four UKFs. Experimental results for
a direct-torque-controlled IM drive are presented and compared
with the EKF. The focus of this study is on low-speed performance.
It is concluded that the UKF is a viable and powerful tool for IM
state estimation and that basic and general UTs give more accurate
results than simplex and spherical UTs.
OriginalsprogEngelsk
TidsskriftI E E E Transactions on Industrial Electronics
Vol/bind59
Udgave nummer11
Sider (fra-til)4207-4216
Antal sider10
ISSN0278-0046
DOI
StatusUdgivet - 2012

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State estimation
Kalman filters
Induction motors
Extended Kalman filters
Nonlinear systems
Torque

Citer dette

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title = "State Estimation of Induction Motor Drives Using the Unscented Kalman Filter",
abstract = "This paper investigates the application, design, andimplementation of unscented Kalman filters (KFs) (UKFs) forinduction motor (IM) sensorless drives. UKFs use nonlinear unscentedtransforms (UTs) in the prediction step in order to preservethe stochastic characteristics of a nonlinear system. Theadvantage of using UTs is their ability to capture the nonlinearbehavior of the system, unlike extended KFs (EKFs) that uselinearized models. Four original variants of the UKF for IMstate estimation, based on different UTs, are described, analyzed,and compared. The four transforms are basic, general, simplex,and spherical UTs. This paper discusses the theoretical aspects andimplementation details of the four UKFs. Experimental results fora direct-torque-controlled IM drive are presented and comparedwith the EKF. The focus of this study is on low-speed performance.It is concluded that the UKF is a viable and powerful tool for IMstate estimation and that basic and general UTs give more accurateresults than simplex and spherical UTs.",
keywords = "Induction machine drives, Kalman filters, sensorless drives, state estimation",
author = "Cristian Lascu and Saeed Jafarzadeh and M.Sami Fadali",
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State Estimation of Induction Motor Drives Using the Unscented Kalman Filter. / Lascu, Cristian; Jafarzadeh, Saeed; Fadali, M.Sami.

I: I E E E Transactions on Industrial Electronics, Bind 59, Nr. 11, 2012, s. 4207-4216.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

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N2 - This paper investigates the application, design, andimplementation of unscented Kalman filters (KFs) (UKFs) forinduction motor (IM) sensorless drives. UKFs use nonlinear unscentedtransforms (UTs) in the prediction step in order to preservethe stochastic characteristics of a nonlinear system. Theadvantage of using UTs is their ability to capture the nonlinearbehavior of the system, unlike extended KFs (EKFs) that uselinearized models. Four original variants of the UKF for IMstate estimation, based on different UTs, are described, analyzed,and compared. The four transforms are basic, general, simplex,and spherical UTs. This paper discusses the theoretical aspects andimplementation details of the four UKFs. Experimental results fora direct-torque-controlled IM drive are presented and comparedwith the EKF. The focus of this study is on low-speed performance.It is concluded that the UKF is a viable and powerful tool for IMstate estimation and that basic and general UTs give more accurateresults than simplex and spherical UTs.

AB - This paper investigates the application, design, andimplementation of unscented Kalman filters (KFs) (UKFs) forinduction motor (IM) sensorless drives. UKFs use nonlinear unscentedtransforms (UTs) in the prediction step in order to preservethe stochastic characteristics of a nonlinear system. Theadvantage of using UTs is their ability to capture the nonlinearbehavior of the system, unlike extended KFs (EKFs) that uselinearized models. Four original variants of the UKF for IMstate estimation, based on different UTs, are described, analyzed,and compared. The four transforms are basic, general, simplex,and spherical UTs. This paper discusses the theoretical aspects andimplementation details of the four UKFs. Experimental results fora direct-torque-controlled IM drive are presented and comparedwith the EKF. The focus of this study is on low-speed performance.It is concluded that the UKF is a viable and powerful tool for IMstate estimation and that basic and general UTs give more accurateresults than simplex and spherical UTs.

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