Unscented Kalman Filter Sensorless Permament Magnet Synchronous Motor Model Predictive Control

Dariusz Janiszewski

doi:10.20944/preprints202311.1907.v2

Preprint Article Version 2 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 27 November 2023 / Approved: 28 November 2023 / Online: 30 November 2023 (07:27:18 CET)
Version 2 : Received: 17 December 2023 / Approved: 18 December 2023 / Online: 18 December 2023 (11:03:29 CET)

The paper deals with the Model Predictive Control (MPC) algorithm as applied to the sensorless control of a Permanent Magnet Synchronous Motor (PMSM). The proposed estimation strategy, based on the unscented Kalman filter (UKF), uses only the measurement of the motor current for the online estimation of speed, rotor position and load torque. Information about the system state feeds the MPC. Results verify the effectiveness and applicability of the proposed sensorless control technique. An implementation in low speed direct drive astronomy telescope mount systems is investigated.

motion control; Automatic control; Predictive control; Sensorless control; Kalman filters; Unscented Kalman filter; System modelling

Engineering, Control and Systems Engineering

Comment 1

Received: 18 December 2023
Commenter: Dariusz Janiszewski
Commenter's Conflict of Interests: Author

Comment: Work corrected after reviewers' comments and colleagues' suggestions. Supplemented with several formulas describing MPC and presenting the ideas of sensorless control.

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Unscented Kalman Filter Sensorless Permament Magnet Synchronous Motor Model Predictive Control

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