An improved fuzzy logic controller design for PV inverters utilizing differential search optimization

This paper presents an adaptive fuzzy logic controller (FLC) design technique for photovoltaic (PV) inverters using differential search algorithm (DSA). This technique avoids the exhaustive traditional trial and error procedure in obtaining membership functions (MFs) used in conventional FLCs. This technique is implemented during the inverter design phase by generating adaptive MFs based on the evaluation results of the objective function formulated by the DSA. In this work, the mean square error (MSE) of the inverter output voltage is used as an objective function. The DSA optimizes the MFs such that the inverter provides the lowest MSE for output voltage and improves the performance of the PV inverter output in terms of amplitude and frequency. The design procedure and accuracy of the optimum FLC are illustrated and investigated using simulations conducted for a 3 kW three-phase inverter in a MATLAB/Simulink environment. Results show that the proposed controller can successfully obtain the desired output when different linear and nonlinear loads are connected to the system. Furthermore, the inverter has reasonably low steady state error and fast response to reference variation.