Implementation of a novel Hebbian least mean square techniques to a Cascaded MLI based SAPF

Abstract

This work represents a novel Hebbian least mean square (H-LMS) technique for a proposed cascaded multilevel inverter-based SAPF. The suggested control technique is applied with the self-learning principle. Active and reactive weights updating is implemented along with DC and AC PI controller output to generate reference compensating current. This reference compensating current is used to create switching pulse signals for the MLI of the SAPF. The behavior of the suggested SAPF is analyzed through MATLAB/Simulink model. The simulation results proved that this SAPF is operating satisfactorily in both balanced and unbalanced nonlinear load conditions.