Improving energy harvesting in photovoltaic systems under partial shading conditions using hybrid fuzzy logic and synergetic control

Partial shading conditions (PSCs) remain one of the major challenges affecting the performance of photovoltaic (PV) systems because they produce multiple local maximum power points, making accurate global maximum power point tracking (GMPPT) difficult for conventional MPPT techniques. This paper proposes a hybrid synergetic–fuzzy logic control (Synergetic–FLC) strategy that combines the adaptive decision-making capability of fuzzy logic with the fast convergence, robustness, and stability of synergetic control to improve MPPT performance under PSCs. The proposed controller is employed to regulate a DC–DC boost converter and is evaluated under various partial shading scenarios using MATLAB/Simulink. Its performance is compared with standalone fuzzy logic control and synergetic control in terms of tracking accuracy, convergence speed, dynamic response, and overall efficiency. Simulation results demonstrate that the proposed hybrid controller consistently achieves faster convergence, reduced steady-state oscillations, and superior tracking performance, reaching a maximum tracking efficiency of 99.84%. In addition to maximizing energy harvesting, the proposed approach enhances the robustness and operational reliability of PV systems operating under rapidly changing environmental conditions. The smoother dynamic response also improves power quality by minimizing oscillations around the global maximum power point, leading to more stable converter operation and improved energy conversion efficiency. These results demonstrate that the proposed hybrid synergetic–FLC strategy provides an effective and reliable solution for high-performance MPPT in partially shaded PV systems while supporting the sustainability and long-term operational efficiency of renewable energy generation.