Performance comparison of classical and fuzzy logic MPPT techniques under sudden irradiation variations and their hardware implementation

This study presents the simulation and experimental implementation of two distinct categories of Maximum Power Point Tracking (MPPT) algorithms aimed at optimizing the performance of Photovoltaic (PV) systems. The first category involves advanced Fuzzy Logic-based MPPT controllers, specifically FL-Mamdani and FLTakagi Sugeno (FL-TS) models. These controllers utilize two input parameters: the gradient of the powercurrent curve and its variation, offering an alternative to conventional methods that depend on the gradient of the power voltage curve and its change. The second category consists of classical MPPT algorithms, including Incremental Conductance (IC) and Perturb and Observe (P&O). The experimental setup comprises a PV system with a TDC-P50-42 solar panel powering a resistive load through a boost converter. The converter’s Mosfet is controlled via a Pulse Width Modulation (PWM) signal generated by the MPPT controller. The algorithms were first simulated using MATLAB/Simulink and then implemented in real-time using an Arduino board supported by the Simulink hardware package for Arduino. Experimental results confirm the proper functioning of the proposed PV system. Among the tested techniques, the FL-TS fuzzy logic controller demonstrated superior performance and reliability, validating its practical applicability in real-world PV applications.