Title: Different artificial intelligence strategies to control an inverter of an active power filter for power quality improvement

Authors: Ouarda Lahmadi; Louiza Benfarhi

Addresses: Department of Electrical Engineering, Batna-2-University, Algeria ' Department of Electrical Engineering, Batna-2-University, Algeria

Abstract: In this paper, performance of active power filter (APF) is analysed for various types of artificial intelligent current controllers which are used to generate switching signals of the voltage source inverter (VSI). Three efficient and reliable intelligent approaches were adopted. The first two are based on a PI-neural regulator and the direct control using a multi-layer perceptron neural network (MLP) respectively. The third one is based on the fuzzy logic regulator. The objective is to take advantages of these intelligent techniques to improve the compensation performance of the conventional APF to minimise harmonic contamination drawn from nonlinear loads, and enhance the power quality. Further, we propose to extend the use of the adaptive linear neuron (ADALINE) in all control schemes to build a homogeneous computing structure. The proposed compensator APF-neural, based on a complete neuromimetic strategy shows its effectiveness and robustness compared to the fuzzy and conventional current controllers.

Keywords: adaptive compensation; artificial intelligent controllers; harmonic current compensation; LMS training algorithm; multi-layer perceptron neural network; MLPNN; shunt active power filter; SAPF; voltage source inverter control; VSI.

DOI: 10.1504/IJPELEC.2020.110749

International Journal of Power Electronics, 2020 Vol.12 No.4, pp.399 - 427

Received: 13 Feb 2018
Accepted: 19 Jun 2018
Published online: 29 Oct 2020 *

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