- Tytuł:
- Dynamic performance of estimator-based speed sensorless control of induction machines using extended and unscented Kalman filters
- Autorzy:
-
Horváth, K.
Kuslits, M. - Powiązania:
- https://bibliotekanauki.pl/articles/1193590.pdf
- Data publikacji:
- 2018
- Wydawca:
- Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
- Tematy:
-
induction machine
speed sensorless control
field-oriented control
FOC
non-linear state estimation
load torque estimation
extended Kalman filter
EKF
unscented Kalman filter
UKF - Opis:
- This paper presents an estimator-based speed sensorless field-oriented control (FOC) method for induction machines, where the state estimator is based on a self-contained, non-linear model. This model characterises both the electrical and the mechanical behaviours of the machine and describes them with seven state variables. The state variables are estimated from the measured stator currents and from the known stator voltages by using an estimator algorithm. An important aspect is that one of the state variables is the load torque and, hence, it is also estimated by the estimator. Using this feature, the applied estimator-based speed sensorless control algorithm may be operated adequately besides varying load torque. In this work, two different variants of the control algorithm are developed based on the extended and the unscented Kalman filters (EKF, UKF) as state estimators. The dynamic performance of these variants is tested and compared using experiments and simulations. Results show that the variants have comparable performance in general, but the UKF-based control provides better performance if a stochastically varying load disturbance is present.
- Źródło:
-
Power Electronics and Drives; 2018, 3, 38; 129-144
2451-0262
2543-4292 - Pojawia się w:
- Power Electronics and Drives
- Dostawca treści:
- Biblioteka Nauki
Artykuł