Abstract
This paper proposes a model-free PID fuzzy logic control for parallel robot. This kind control differs from conventional classical and modern control techniques, even existed intelligent controls. Nor precise description of dynamics model neither physical parameter is required for construction of the fuzzy control. Takagi-Sugeno-Kang (TSK) fuzzy approach with extended subtractive clustering computing is used to accomplish the integration of information of joint angular displacement, velocity and acceleration for torque identification where the learning datasets are generated by using a PID feedback control. The fuzzy inference system is used for design the nouvelle model-free PID fuzzy feed forward control for the parallel mechanism. Simulation results from numerical study on a 4-bar planar parallel mechanism show the proposed control can reduce joint position and velocity tracking errors with high accuracy and high reliability.
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