Comparison of nonlinear Kalman filtering schemes for sensorless control of permanent magnet-assisted synchronous reluctance machines
Permanent magnet-assisted synchronous reluctance machines (PMA-SynRMs) are gaining attention thanks to their cost-effectiveness, reliability, and efficiency. Speed-sensorless control methods can provide additional competitive advantages to these machines, such as cost and size reduction, and reliabi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-04-01
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| Series: | International Journal of Electrical Power & Energy Systems |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061525000389 |
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| Summary: | Permanent magnet-assisted synchronous reluctance machines (PMA-SynRMs) are gaining attention thanks to their cost-effectiveness, reliability, and efficiency. Speed-sensorless control methods can provide additional competitive advantages to these machines, such as cost and size reduction, and reliability enhancement. In this sense, Kalman filter theory (KF) constitutes a well-established solution for sensorless control of electrical drives that can be easily combined with model predictive control schemes (MPC). This study compares the extended and unscented KF formulations (EKF and UKF) in a sensorless MPC of a PMA-SynRM drive. Performance, computational effort, and sensitivity to measurement errors and model parameters are evaluated and compared through simulation to clarify which filtering algorithm is more suitable for the system under study. |
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| ISSN: | 0142-0615 |