Recently, Sustainable energy has appeared recently as one of the most efficient sources of electrical energy. Solar energy, which converts direct sun rays into electrical energy, is one of the most basic kind of renewable energy. Maximum power extraction in the presence of changing environmental conditions is one of the problems of solar energy transformation. The Weather conditions affectthe voltage, current, and consequently the maximum power extracted from PV panels. To raise the efficiency and reducing the tracking time of the system, it requests to work for PV panels at a Maximum Power Point (MPP). Under any environmental conditions, there is a different MPP. Solar irradiation, temperature, and load all affect the PV panel's output power. The control of a Photovoltaic system using fuzzy logic, intelligent Maximum Power Point Tracking (MPPT) is proposed in this study. Fuzzy MPPT systems have a rapid response to the changes in the environmental conditions and do not move with changes in circuit parameters. In this research, we compare different examples of membership functions like Triangular, PIShaped, and Gaussian combination with different roles. Simulation results show that the Pi-shaped membership function has the best performance compared to other types. Fuzzy MPPT controller based on PI-shaped membership function is designed and implemented using low-cost hardware. Experimental results confirmed the validity of the proposed MPPT system.