Title :
The research of PMSM drive based on wavelet neural network space vector PWM
Author :
Baoping, Cai ; Yonghong, Liu ; Qiang, Lin ; Haifeng, Zhang
Author_Institution :
Coll. of Mech. & Electron., China Univ. of Pet., Dongying, China
Abstract :
The basid principle of space vector pulse width modulation (SVPWM) is analyzed, and a algorithm of SVPWM based on wavelet neural network (WNN-SVPWM) is proposed. The comparative study between BP neural network space vector pulse width modulation (BP-SVPWM) and WNN-SVPWM is done. The simulation results show that the permanent magnet synchronous motor (PMSM) controlled by WNN-SVPWM has less total current harmonic distortion and pulsating torque than BP-SVPWM. The closed-loop PMSM control system controlled by WNN-SVPWM is researched, and the experimental results show that the voltage and current waves are perfect, and the motor works well.
Keywords :
backpropagation; closed loop systems; electric machine analysis computing; harmonic distortion; machine control; permanent magnet motors; synchronous motors; BP neural network space vector pulsewidth modulation; BP-SVPWM; PMSM drive; backpropagation; closed-loop PMSM control system; current waves; permanent magnet synchronous motor; pulsating torque; total current harmonic distortion; voltage waves; wavelet neural network space vector PWM; Algorithm design and analysis; Control systems; Functional analysis; Magnetic analysis; Neural networks; Permanent magnet motors; Space vector pulse width modulation; Torque control; Voltage control; Wavelet analysis; PMSM; SVPWM; current harmonic distortion; pulsating torque; wavelet neural network;
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
DOI :
10.1109/ICICISYS.2009.5357934
