Parameter adaptive for PMSM sensorless speed control

This paper aims at reducing the effects caused by the model parameter variations in the permanent magnet synchronous motor(PMSM) sensorless speed control. A model parameter adaptive observer is proposed, which utilizes the dual unscented Kalman filter (DUKF) to estimate system states and model parameters. The experimental results show that DUKF based observer estimates the system states and model parameters efficiently and accurately in the PMSM sensorless speed control. This control scheme has achieved the expected performance with model parameter adaptation.