Research on online parameter identification of interior permanent magnet synchronous motor based on augmented robust forgetting factor recursive least square

2020 ◽  
Vol 31 (12) ◽  
Author(s):  
Yafu Zhou ◽  
Hantao Wang ◽  
Jing Lian
2011 ◽  
Vol 383-390 ◽  
pp. 5940-5944
Author(s):  
Song Wang ◽  
Rui Jie Zhao ◽  
Wei Min Chen ◽  
Guang Da Li ◽  
Chao Liu

In this paper, two least square algorithms, Recursive Least Square (RLS) and Windowed Least Square (WLS) are applied to identify the parameters varying with temperature of Permanent Magnet Synchronous Motor (PMSM). In order to compare the identification effects of the two algorithms, a PMSM model is built and simulated in MATLAB. And simulation results demonstrate that WLS guarantees better timeliness and rapidity.


2007 ◽  
Author(s):  
Tomonobu Senjyu ◽  
Yohei Noguchi ◽  
Naomitsu Urasaki ◽  
Atsushi Yona ◽  
Hideomi Sekine

2012 ◽  
Vol 588-589 ◽  
pp. 479-483
Author(s):  
Song Wang ◽  
Guang Da Li

A new method named Windowed Least Square (WLS) to test main parameters of Permanent Magnet Synchronous Motor (PMSM) is proposed in this paper. Compared with Extended Kalman Filter (EKF) & Elman neural network and Recursive Least Square (RLS), WLS guarantees identification accuracy and excellent timeliness, and the issue of data saturation of RLS can be avoided. The PMSM model is built combining on-line parameter identification with Active Disturbance Rejection Control (ADRC) to improve the control performance of PMSM. The simulation results demonstrate that the performance of ADRC system using online estimation strategy is better than that of the system using PID method.


2009 ◽  
Vol 37 (8) ◽  
pp. 847-865 ◽  
Author(s):  
Naomitsu Urasaki ◽  
Yohei Noguchi ◽  
Abdul Motin Howlader ◽  
Yuri Yonaha ◽  
Atsushi Yona ◽  
...  

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