DocumentCode :
729413
Title :
Position estimation at zero speed for PMSM using probabilistic neural network
Author :
Urbanski, Konrad
Author_Institution :
Inst. of Control & Inf. Eng., Poznan Univ. of Technol., Poznan, Poland
fYear :
2015
fDate :
24-26 June 2015
Firstpage :
427
Lastpage :
432
Abstract :
The paper presents a method for estimating the shaft position of a synchronous motor with permanent magnets (PMSM) for the zero and very low speed range. The method is based on the analysis of the high frequency currents, which are induced by the additional test voltage in a stationary coordinate system associated with the stator. Although this method involves the identification of currents hodograph, the method does not need to calculate the current ellipse position. Presented method involves a comparison of obtained shape to the reference pattern using probabilistic neural network (PNN). The method can achieve satisfactory accuracy in a case the high asymmetry of the inductance, as well as in the case of small values of the inductance asymmetry ratio, also in the case of a high level of noise.
Keywords :
estimation theory; inductance; neural nets; permanent magnet motors; power engineering computing; probability; shafts; synchronous motors; PMSM; PNN; current ellipse position; current hodograph identification; inductance asymmetry; permanent magnet synchronous motor; probabilistic neural network; shaft position estimation; zero speed; Estimation; Frequency measurement; Inductance; Noise; Rotors; Shafts; Shape; artificial neural network; estimation; permanent magnets synchronous motor; probabilistic neural network; sensorless control; zero speed;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on
Conference_Location :
Gdynia
Print_ISBN :
978-1-4799-8320-9
Type :
conf
DOI :
10.1109/CYBConf.2015.7175972
Filename :
7175972
Link To Document :
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