This chapter presents a highly efficient proportional-integral controller aiming to track the Maximum Power Point in a Photovoltaic (PV) system. This controller is based on an adaptive multi-model structure composed of eight local models scaled by nonlinear weighting functions and obtained from the polytopic transformation of the PV system’s state model. Each local model is calculated online according to the extreme values of temperature and irradiance to which the PV system can be exposed. A partial PI controller is developed for each local model to guarantee effective Maximum Power Point tracking. Gains of the eight partial controllers are weighted by the corresponding nonlinear weighting functions and then fused to compute the PV system PI controller. The developed controller has succeeded in guaranteeing accurate tracking of the MPP under changing temperature and irradiance and has demonstrated exceptional performance in attaining stable, non-oscillatory, and quick response as shown by the simulation results. The suggested approach shows notable benefits over the conventional Perturb and Observe-based MPPT controller for the considered environmental profiles and is affordable and compatible with micro-computing platforms, making it a viable option for scalable and dependable PV applications.