A Comparative Analysis of the Mamdani and Sugeno Fuzzy Inference Systems for MPPT of an Islanded PV System

With the maturation of nonlinear systems, considerable endeavors have been made to provide valid and high-speed controllers supervise superior more complex systems. Artificial intelligence has remembered as head topic among designers in last decade. One popular control techniques is fuzzy logic, which known a controller that simulates behavior an expert operator. On other hand, due necessity change human energy sources popularity solar energy, attention greatest utilization this category green resources significantly increased. Maximum power point tracking (MPPT) systems headed topic, with innovative methods being presented every day despite numerous articles. However, less discussed choice inference system. In article, two classes Mamdani Sugeno are introduce best for extracting from system by implementing both types gaining understanding their differences. addition, influence number input membership functions on performance investigated. Therefore, different given each model. It should be noted setup done genetic algorithm respond mortal desire automate various processes, subset artificial intelligence. Accordingly, four designed implemented The results were tested summarized radiations MATLAB Simulink.