Abstarct: Researchers have suggested several choices, the cardinal of solar energy, looking for alternatives to fossil fuels as a primary electricity source. To implement this proposal, features like productivity must be facilitated. One of the most critical challenges in this field is the nonlinear and environmental characteristics of the panel. Reaching an apposite operating point is noted as one of the various ways of achieving this goal known as Maximum Power Point Tracking (MPPT), an attractive topic to experts. This research presents a new fuzzy-baxsed method for continuous tracking of maximum power points in different radiations, temperatures, and loads. This method contains a fuzzy logic controller, which is simplified and optimized with three different mextaheuristic algorithms. The results are compared with a classic method (Hill Climbing), which is gradient baxse. Also, among optimization algorithms, two unwell-known algorithms, which are Imperialist Competitive Algorithm (ICA) and Invasive weed Algorithm (IWO), are compared with the Genetic Algorithm (GA), one of the algorithms that experts frequently use. In designing the fuzzy controller system, two significant issues have been considered: the most important of them is the minimization of control parameters while maintaining the output power at the apex. Another issue is the complexity of designing a fuzzy controller, which is closely related and unique for each system. An adaptable fuzzy controller is represented to overcome this difficulty, which can work properly with all PV systems with minimum changes.