Combination of artificial neural network and flower pollination algorithm to model fuzzy logic MPPT controller for photovoltaic systems

In this paper, a new hybrid model is proposed to control the DC/DC converter of Grid Connected Photovoltaic System. The approach used to build the developed controller is divided into three steps, the first step is to generate a data based on the fuzzy logic controller (FLC), the second step is to choose an artificial neural network (ANN) structure to model the FLC and the last step is the training process of the ANN model which is performed by the flower pollination algorithm (FPA). This algorithm is based on the optimization of the root mean square error between the FLC and the ANN models. A validation test of the proposed controller was carried with various irradiations under any weather conditions.