In this paper, a model predictive control algorithm is developed for the regulation problem of a biaxialfeed drive system. The orthogonal error component in the moving frame is considered as an approximation ofthe real contour error. Then, the control policy is derived from the worst-case optimization of a quadratic costfunction, which penalizes transformed errors, velocity errors and control variables in each sampling time overa finite horizon. In addition, the constraint is satisfied to ensure the convergence against uncertain but boundeddisturbances. The good performance of the proposed control algorithm is verified via computer simulations withpredefined trajectories. Furthermore, the result shows the improvement of the tracking accuracy by comparing withthe unconstrained predictive control methods