Takagi–Sugeno Fuzzy Modeling and Control for Effective Robotic Manipulator Motion

Robotic manipulators are widely used in applications that require fast and precise motion. Such devices, however, prompt to nonlinear control issues due the flexibility joints friction motors within dynamics of their rigid part. To address these issues, Linear Matrix Inequalities (LMIs) Parallel Distributed Compensation (PDC) approaches implemented Takagy-Sugeno Fuzzy Model (T-SFM). We propose following methodology; initially, state space equations manipulator model derived. Next, a (T-SFM) technique is for linearizing manipulator. The T-SFM controller developed using method. prime concept designed compensate all fuzzy rules. Furthermore, applied generate adequate cases ensure stability control. Convex programming methods solve LMIs problems. Simulations proposed show stabilized system with zero tracking error less than 1.5 s.