Adaptive directive neural network control for three-phase AC/DC PWM converter

Author

Cheng, K.W.E. ; Wang, H.Y. ; Sutanto, D.

Author_Institution

Dept. of Electr. Eng., Hong Kong Polytech. Univ., Kowloon, China

Volume

148

Issue

5

fYear

2001

fDate

9/1/2001 12:00:00 AM

Firstpage

425

Lastpage

430

Abstract

A novel control strategy is proposed: adaptive B-spline neural network for three-phase AC/DC voltage source converters, which realises a sinusoidal AC input current and unity power factor. Compared with other PWM techniques, neural network control provides an excellent component of a nonlinear system and is adaptive enough to fit the environment change. An online B-spline neural network is used because of its local weight updating characteristic, which has the advantages of fast convergence speed and low computation complexity. This is very important for real-time control applications. Both simulation and experimental results are presented to verify the effectiveness of the proposed control strategy

Keywords

AC-DC power convertors; PWM power convertors; adaptive control; control system analysis; control system synthesis; neurocontrollers; rectifying circuits; splines (mathematics); voltage control; adaptive B-spline neural network; adaptive directive neural network control; computation complexity; control design; control performance; control simulation; convergence speed; local weight updating characteristic; real-time control applications; sinusoidal AC input current; three-phase AC/DC PWM power converter; unity power factor; voltage source converters;

fLanguage

English

Journal_Title

Electric Power Applications, IEE Proceedings -

Publisher

iet

ISSN

1350-2352

Type

jour

DOI

10.1049/ip-epa:20010564

Filename

955377