<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></abstract>

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.

Dynamic Performance of Estimator-based Speed Sensorless Control of Induction Machines Using Extended and Unscented Kalman Filters

Power Electronics and Drives

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

This paper presents an estimator-based speed sensorless field-oriented control (FOC) method for induction machines, where the state estimator is based on a...

Dynamic Performance of Estimator-based Speed Sensorless Control of Induction Machines Using Extended and Unscented Kalman Filters

Article Category: Special Section on Sensorless Drives

Online veröffentlicht: 17. Nov. 2018

Seitenbereich: 129 - 144

Eingereicht: 30. Aug. 2017

Akzeptiert: 21. März 2018

DOI: https://doi.org/10.2478/pead-2018-0003

Schlüsselwörter
Induction machine, speed sensorless control, field-oriented control (FOC), non-linear state estimation, load torque estimation, extended Kalman filter (EKF), unscented Kalman filter (UKF)

© 2018 Krisztián Horváth, Márton Kuslits, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Dynamic Performance of Estimator-based Speed Sensorless Control of Induction Machines Using Extended and Unscented Kalman Filters

Article Category: Special Section on Sensorless Drives

Online veröffentlicht: 17. Nov. 2018

Seitenbereich: 129 - 144

Eingereicht: 30. Aug. 2017

Akzeptiert: 21. März 2018

DOI: https://doi.org/10.2478/pead-2018-0003

SchlüsselwörterInduction machine, speed sensorless control, field-oriented control (FOC), non-linear state estimation, load torque estimation, extended Kalman filter (EKF), unscented Kalman filter (UKF)

© 2018 Krisztián Horváth, Márton Kuslits, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Induction machine, speed sensorless control, field-oriented control (FOC), non-linear state estimation, load torque estimation, extended Kalman filter (EKF), unscented Kalman filter (UKF)