Practical specification of the speech universe of the maximum power point tracking controller based on the asymmetrical fuzzy logic: a dynamic behavior study of the photovoltaic system

In this paper, we present a procedure for extracting data from a stand-alone photovoltaic (PV) panel to program a maximum power point tracking (MPPT) controller based on the fuzzy logic (FL) method, aiming to optimize the performance of the photovoltaic system. Photovoltaic data acquisition enables the determination of the input and output speech universe for the MPPT controller using fuzzy logic. This method adapts to nonlinear systems without requiring a complex mathematical model. Additionally, it improves the performance of the photovoltaic system in both dynamic and steady-state conditions. To further enhance the method’s efficiency, an asymmetric membership function concept is proposed based on the dynamic behavior study of the photovoltaic system. Compared to the symmetric method, the asymmetric fuzzy logic controller achieves higher maximum power output and better tracking precision. This technology is essential for maximizing photovoltaic panel efficiency, a key requirement as solar energy gains prominence as a clean and renewable energy source.