Abstract
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.
Original language | English |
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Pages (from-to) | 95-98 |
Number of pages | 4 |
Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
Volume | 30 |
Issue number | SUPPL. 1 |
Publication status | Published - Jun 2010 |
Keywords
- Dual unscented Kalman filter(DUKF)
- Parameter adaptation
- Permanent magnet synchronous motor(PMSM)
- Sensorless speed control