Adaptive linear neuron control of three-phase shunt active power filter with anti-windup PI controller optimized by particle swarm optimization

In the present paper, particle swarm optimization technique (PSO) is used to tune anti-windup PI controller gains for DC bus voltage control of the shunt active power filter by offline simulation. The main advantage of the PSO tuning algorithm is to accurately estimate PI controller parameters and overcome the complexity of analytical calculation approaches as well as classical tuning methods. The sum of the total harmonic distortion of source currents and the DC bus's voltage error are used as a fitness function. The reference current is obtained using an artificial neural network named adaptive linear neuron (ADALINE). Three ADALINEs are trained online using the least mean square algorithm (LMS). The proposed system is designed by MATLAB/Simulink and validated experimentally through the dSPACE DS1104 platform. The analysis is done for various conditions, and the obtained results demonstrate the effectiveness of the controller in terms of performance, efficiency, and power quality enhancement.