Support-centric PSO-based fuzzy MPPT tuning for photovoltaic systems under uniform conditions - Smaili, Amel; Boudissa, El-Ghalia; Bounekhla, M’hamed (Institute of Advanced Engineering and Science, 2025)
Several conventional maximum power point tracking (MPPT) algorithms have been applied to harvest the optimal power of a photovoltaic (PV) system. However, the main drawbacks of these algorithms are their fluctuations around the maximum power point (MPP) and their dependence on climatic conditions variation. To overcome these issues, a fuzzy logic controller (FLC) is proposed, where the system performance depends strongly on the choice of membership functions (MFs). They are typically selected by trial and error, which may not always yield the best results. This paper seeks to enhance the efficiency of the traditional FLC method by using the particle swarm optimization (PSO) algorithm for optimizing the supports of the triangular MFs. The simulation was performed using MATLAB-Simulink environment using the