DocumentCode :
2455131
Title :
Sensorless stator flux oriented control of IMS using a new Delayed-State KF-based algorithm
Author :
Salvatore, N. ; Cascella, G.L. ; Stasi, S. ; Cascella, D.
Author_Institution :
DEE, Politec. di Bari, Bari
fYear :
2008
fDate :
15-19 June 2008
Firstpage :
37
Lastpage :
42
Abstract :
This paper proposes a new reduced delayed-state Kalman filter (DSKF) based algorithm to realize the speed-sensorless vector control of induction motor. This algorithm estimates the stator flux components in the stationary reference frame, using the derivatives of the stator flux components as mathematical model and the stator voltage equations as observation model. The DSKF-based algorithm accurately estimates the stator flux components in transient operations because the derivative of the absolute stator flux value is taken into account as a forcing term in the mathematical model, so that applications both in flux rising operations and in field weakening region are possible. The estimated stator flux components are used for stator field orientation control (SFOC) without rotor speed sensor. Experiments show that the sensorless control scheme using the new DSKF-based algorithm requires a low computational effort, is stable and effective also at low speeds.
Keywords :
Kalman filters; induction motors; machine vector control; stators; IM; delayed-state KF-based algorithm; delayed-state Kalman filter based algorithm; field weakening region; flux rising operations; induction motor; mathematical model; sensorless stator flux oriented control; speed-sensorless vector control; stationary reference frame; stator field orientation control; stator flux components; stator voltage equations; Couplings; Delay; Equations; Induction motors; Kalman filters; Mathematical model; Position control; Sensorless control; Stators; Voltage; Kalman filter; induction motor; sensorless;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Electronics Specialists Conference, 2008. PESC 2008. IEEE
Conference_Location :
Rhodes
ISSN :
0275-9306
Print_ISBN :
978-1-4244-1667-7
Electronic_ISBN :
0275-9306
Type :
conf
DOI :
10.1109/PESC.2008.4591893
Filename :
4591893
Link To Document :
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