Combination of ANFIS, PSO, FCN and Fuzzy Controller for MPPT of Photovoltaic Arrays

In this paper, an on-line method for maximum power point tracker using fuzzy set theory is presented to improve energy conversion efficiency. This method is proposed, by using a fuzzy cognitive network, which is in close cooperation with the presented fuzzy controller. The proposed approach is based on the combination of Particle Swarm Optimization (PSO) and Adaptive-Network-based Fuzzy Inference Systems (ANFIS) methods, and it is used for the determination of proper weight matrices that lead the Fuzzy Cognitive Map to desired steady states. The method gives a good maximum power operation of any PV. The advantage of the presented method is that the control system can adapt to different changes that might happen during the life cycle of the PV module. All the analytical and simulation results of this research are presented.

Keywords:

Adaptive-Network-based Fuzzy Inference Systems (ANFIS) , fuzzy cognitive networks (FCN) , fuzzy controller , maximum power point tracker (MPPT) , Particle Swarm Optimization (PSO