Investigation of Rotor Position and Speed Self-Sensing for PMSM Based On Grey Prediction
For the fact that the running of permanent magnet synchronous motor has a strong characteristic of periodicity and orderliness, the new rotor position and speed self-sensing technique is proposed using grey system prediction theory. The valid predictors which are the diagram of curve of magnetic flux linkage--stator current--rotor position and the diagram of curve of back electromotive force (back-EMF)--virtual value of voltage--rotor speed are chosen by grey correlation analysis. Then the rotor position was predicted by the five curves using equidistant interval GM(1,1) prediction model and the rotor speed was predicted using non-equidistant interval GM(1,1) prediction model according to the different speed range. Sensorless vector control was investigated using the proposed method. Simulation results reveal the effectiveness of state estimation and robustness for parameter variations, the control system has a good static and dynamic performance.
Degree of grey correlation(DGC) grey system prediction permanent-magnet synchronous motors(PMSM) rotor position self-sensing sensorless vector control valid predictor
Xiaohui Zhu Yinghui Li
Department of Aeronautic Automatic Control, Air Force Engineering University, Xi’an, Shanxi 710038 China
国际会议
The International Conference on Electrical Engineering 2009(2009 电机工程国际会议)
沈阳
英文
1-6
2009-07-05（万方平台首次上网日期，不代表论文的发表时间）