A Novel Nonlinear Intelligent Control Approach for Optimizing Solar PV Systems in Medical Applications under Dynamic Conditions

Abstract

Medical equipment reliability is crucial, demanding consistent power supply. Photovoltaic (PV) systems face challenges in optimizing power output, particularly under fluctuating environmental conditions. To address this, we propose a novel Maximum Power Point Tracking (MPPT) technique integrating Adaptive Neuro-Fuzzy Inference System (ANFIS) and Fast Terminal Synergetic Controller (FTSC). This hybrid approach balances adaptability with stability and rapid response times. Achieving $\mathbf{9 9 . 8 9 \%}$ efficiency, with only a marginal deviation of $2.79 \%$ compared to conventional FTSC techniques and a notable improvement of $4.29 \%$ under Ropp test irradiance conditions. Moreover, it demonstrates a rapid response time of 37 ms, surpassing conventional FTSC methods by 48 ms and outperforming P&O approaches by 83 ms. This approach enhances PV system performance, especially critical for medical applications, ensuring uninterrupted power supply for essential equipment.