Development of iterative learning control strategy for active power filter

Author

Xiaoming, Zha ; Qian, Tao ; Jianjun, Sun ; Yunping, Chen

Author_Institution

Sch. of Electr. Eng., Wuhan Univ., China

Volume

1

fYear

2002

fDate

2002

Firstpage

240

Abstract

The paper introduces iterative learning control strategy to active power filter (APF). The control strategy can incorporate feedback and feedforward into the controller of APF and it can enhance the tracking speed, simplify the configuration of the controller and obtain a fast and simple algorithm. The strategy with good robustness can realize self-optimizing and self-stabilizing of the system. It is suitable for the hybrid passive filter and APF The simulation and experiment results are given in the paper.

Keywords

active filters; feedback; feedforward; iterative methods; learning systems; passive filters; power harmonic filters; power system harmonics; self-adjusting systems; stability; active power filter; control strategy; feedback; feedforward; harmonics; hybrid filter; iterative learning control strategy; passive filter; power system harmonics; robustness; system self-optimization; system self-stabilization; tracking speed enhancement; Active filters; Control systems; Hybrid power systems; Passive filters; Power filters; Power harmonic filters; Power system control; Power system harmonics; Power system simulation; Power systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 2002. IEEE CCECE 2002. Canadian Conference on

ISSN

0840-7789

Print_ISBN

0-7803-7514-9

Type

conf

DOI

10.1109/CCECE.2002.1015214

Filename

1015214