Title :
Initial rotor position estimation of salient-pole brushless DC motors by artificial neural network
Author :
Senjyu, Tomonobu ; Urasaki, Naonitsii ; Uezato, K.
Author_Institution :
Fac. of Eng., Ryukyus Univ., Okinawa, Japan
Abstract :
This paper presents an initial rotor position estimation method for salient-pole brushless DC motors (BLDCMs). An artificial neural network (ANN) is employed as an estimator of BLDCM at standstill. The ANN can express the relationship between the voltage and current of BLDCMs. The initial rotor position can be estimated by using only the current-signals from the ANN. The proposed method has the advantages of measurement noise immunity as well as no sensitivity to machine parameters. Computer simulation results verify the usefulness of the proposed method
Keywords :
brushless DC motors; control system analysis computing; electric machine analysis computing; machine control; neurocontrollers; parameter estimation; position control; rotors; artificial neural network; computer simulation; initial rotor position estimation; machine parameters insensitivity; measurement noise immunity; neurocontrol; salient-pole brushless DC motors; standstill; Artificial neural networks; Brushless DC motors; Computer simulation; DC motors; Electronic mail; Feeds; Noise measurement; Rotors; Service robots; Voltage;
Conference_Titel :
Power Conversion Conference - Nagaoka 1997., Proceedings of the
Conference_Location :
Nagaoka
Print_ISBN :
0-7803-3823-5
DOI :
10.1109/PCCON.1997.645601
