Application of an artificial neural network to harmonic reduction in PWM AC-DC converter

Author

Mohaddes, M. ; Gole, A.M. ; McLaren, P.G.

Author_Institution

Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada

Volume

1

fYear

1995

fDate

15-16 May 1995

Firstpage

123

Abstract

Current harmonics in a PWM bidirectional AC-DC power converter are reduced considerably by using a feedforward artificial neural network. The network calculates the exact switching angles for the power converter to eliminate selected harmonics. The number of switching actions and hence the switching losses, are much smaller compared to the other PWM techniques. The control scheme of the power converter is discussed

Keywords

AC-DC power convertors; PWM power convertors; electric current control; feedforward neural nets; neurocontrollers; power system harmonics; rectifying circuits; PWM bidirectional AC-DC power converter; control design; current harmonics control; feedforward artificial neural network; harmonic reduction; selective harmonic elimination; switching angles; switching losses; AC-DC power converters; Analog-digital conversion; Artificial neural networks; Inductors; Intelligent networks; Power harmonic filters; Power system harmonics; Pulse width modulation; Pulse width modulation converters; Voltage;

fLanguage

English

Publisher

ieee

Conference_Titel

WESCANEX 95. Communications, Power, and Computing. Conference Proceedings., IEEE

Conference_Location

Winnipeg, Man.

Print_ISBN

0-7803-2725-X

Type

conf

DOI

10.1109/WESCAN.1995.493957

Filename

493957