DocumentCode :
2341923
Title :
Neural network vector control of a permanent magnet synchronous motor drive
Author :
Wang, Jian ; Wang, Honghua ; Zhang, Xueqin ; Wang, Jiangtao
Author_Institution :
Inst. of Electr. Eng., Hohai Univ., Nanjing
fYear :
2008
fDate :
3-5 June 2008
Firstpage :
542
Lastpage :
546
Abstract :
After analyzing the basic principle of vector control in permanent magnet synchronous motor (PMSM) drive, this paper proposes a novel artificial neural network (ANN) based vector control. Here, ANN is used in speed control and space vector pulse width modulation (SVM), since an artificial neural network based speed controller does not rely on the accurate mathematical model of system, and it has not only fast dynamic response but also high steady-state accuracy, while an artificial neural network based SVM (ANN-SVM) algorithm can be realized easily with a small amount of calculation and efficiently-reduced current harmonic. A PMSM drive simulation model with ANN based vector control is created and studied using Matlab/Simulink. The simulation results demonstrate the feasibility and validity of ANN based vector control.
Keywords :
control engineering computing; machine vector control; neurocontrollers; permanent magnet motors; power engineering computing; support vector machines; synchronous motor drives; velocity control; SVM; artificial neural network; neural network vector control; permanent magnet synchronous motor drive; space vector pulse width modulation; speed control; Artificial neural networks; Machine vector control; Magnetic analysis; Mathematical model; Neural networks; Permanent magnet motors; Space vector pulse width modulation; Steady-state; Support vector machines; Velocity control; ANN; PID; PMSM; SVM; Vector control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1717-9
Electronic_ISBN :
978-1-4244-1718-6
Type :
conf
DOI :
10.1109/ICIEA.2008.4582574
Filename :
4582574
Link To Document :
بازگشت