Dissimilarity Clustering Algorithm for Designing the PID-like Fuzzy Controllers

Fuzzy logic controller is one of the most prominent research fields to improve efficiency for process industries, which usually stick conventional proportional-integral-derivative (PID) control. The paper proposes an improved version three-term PID-like fuzzy by removing necessity having user-defined parameters in place algorithm work. resulting non-parametric dissimilarity-based clustering was shown be very efficient and fast. performance study conducted simulation on armature-controlled field-controller DC motors, linguistic type Takagi-Sugeno-Kang (TSK) models. Comparison created with c-means resulted accuracy, increased speed enhanced robustness, especially high increase TSK model.