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

摘要

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.