Application of predictive control techniques within parallel robot

Abstract

This paper addresses the position tracking control application of a parallel robot using predictive control techniques. A Generalized Predictive Control strategy (GPC), which considers the linear dynamic model, is used to enhance the tracking position accuracy. The robustification of GPC against measurement noise and neglected dynamics using Youla parameterization is performed. A simulation of the orthoglide robot considering uncertainties related to geometrical and dynamic parameters, sensors noise and frictions is performed on two different trajectories. Finally, it is compared the ro-bustified GPC controller with the classical Computed Torque Control (CTC). The robustified GPC controller shows a better performance for high accelerations and it also reduces the effect of the noise in the control signal of the parallel robot

The study of model predictive control algorithm based on the force/position control scheme of the 5-DOF redundant actuation parallel robot

“…MPC uses the online rolling optimization and feedback correction strategy. The online rolling optimization strategy can compensate the uncertainty influence caused by model mismatch and interference so as to improve the control effect of the system [23]- [25]. After a series of future control variables are determined by the optimization, MPC uses the detected error between actual output and the model prediction output to realize feedback correction to remedy the defect.…”