Performance Analysis of Fuzzy Logic Controllers Having Mamdani and Takagi-Sugeno Inference Methods By Using Unique Software and Toolbox
Sinan Unsal, Ibrahim Aliskan, None None
proceeding (Uluslararası, Hakemli) | Yazar(lar): Sinan Unsal, Ibrahim Aliskan, None None | Yıl: 2016 | Dergi/Kurum: 2016 NATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS AND BIOMEDICAL ENGINEERING (ELECO) | İndeks: WOS.ISTP — Özet: Fuzzy logic controllers are structurally consisted of fuzzification, rule based inference
Fuzzy logic controllers are structurally consisted of fuzzification, rule based inference mechanism and defuzzification units. Membership functions and inference methods are important factors that directly effect the performance of controller. In the literature, there are several membership functions and inference methods in different structures. In the performed study, speed control of permanent magnet synchronous motor has been made with fuzzy logic controllers having Mamdani and Takagi-Sugeno inference methods. In the studies, performances of the fuzzy logic controllers that are realized by using unique softwares and toolboxes have been analyzed under different operating conditions. When the obtained results have been evaluated, It has been seen that designed controllers provide consistent results with each other.