The Use of LMS and RLS Adaptive Algorithms for an Adaptive Control Method of Active Power Filter

Abstract

This paper deals with the adaptive control mechanism management meant for shunt active power filters (SAPF). Systems driven this way are designed to improve the quality of electric power (power quality) in industrial networks. The authors have focused on the implementation of two basic representatives of adaptive algorithms , f irst, the algorithm with a stochastic LMS (least mean square) gradient adaptation and then an algorithm with recursive RLS (recursive least square) optimal adaptation. The system examined by the authors can be used for non-linear loads for appliances with rapid fluctuations of the reactive and active power consumption. The proposed system adaptively reduces distortion, falls (dip) and changes in a supply voltage (flicker). Real signals for measurement were obtained at a sophisticated, three-phase experimental workplace. The results of executed experiments indicate that, with use of the certain adaptive algorithms, the examined AHC system shows very good dynamics, resulting in a much faster transition during the AHC connection-disconnection or during a change in harmonic load on the network. The actual experiments are evaluated from several points of view, mainly according to a time convergence (convergence time) and mistakes in a stable state error (steady state error) of the investigated adaptive algorithms and finally as a total harmonic distortion (THD). The article presents a comparison of the most frequently used adaptive algorithms.