Model Predictive Control for Position Tracking of Robot Manipulator

This paper presents the methods for position tracking of the manipulator based on the model predictive control approach. Benefiting from characteristic of predictive control-a procedure for a finite horizon optimal control problem-this method count the control energy reaches its least in mutative control use of a posteriori minimal control when range. Moreover, the and a priori numerical information, which is readily available in the scheme, is evaluated through the computed closed-loop trajectories. Being different from the conventional MPC, the predictive model used in this paper is non-linear. The key attribute of scheme presented is an internal model, on which the predictive control updates with each certain angle-range changing. Although compute needs support of hardware, the effectiveness of the proposed scheme can be concluded if this approach be applied to the eye-to-hand RR manipulator system.