An Artificial Neural Network Based SVPWM Controller for PMSM Drive

Author

Cai Baoping ; Liu Yonghong ; Lin Qiang ; Zhang Haifeng

Author_Institution

Coll. of Mech. & Electron., China Univ. of Pet., Dongying, China

fYear

2009

fDate

11-13 Dec. 2009

Firstpage

1

Lastpage

5

Abstract

In order to research the influence of hidden layer neurons of artificial neural network (ANN) and switching frequency of power switches on the performance of permanent magnet synchronous motor(PMSM), a algorithm of space vector pulse width modulation based on artificial neural network (ANN-SVPWM) is proposed. The simulation and experiment of closed-loop PMSM control system are done. The results show that the PMSM generates less current harmonic distortion and pulsating torque by choosing the optimum hidden neurons of ANN and switching frequency of power switches, and the PMSM controlled by ANN-SVPWM works well.

Keywords

artificial intelligence; closed loop systems; control engineering computing; harmonic distortion; machine control; neural nets; permanent magnet motors; synchronous motor drives; PMSM drive; SVPWM controller; artificial neural network; closed-loop PMSM control system; current harmonic distortion; permanent magnet synchronous motor drive; power switches; pulsating torque; space vector pulse width modulation; switching frequency; Artificial neural networks; Control system synthesis; Harmonic distortion; Neurons; Pulse width modulation inverters; Space vector pulse width modulation; Switches; Switching frequency; Torque; Voltage;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4507-3

Electronic_ISBN

978-1-4244-4507-3

Type

conf

DOI

10.1109/CISE.2009.5366578

Filename

5366578