This paper presents a data-driven model predictive control scheme for the path following and terminal force control of manipulators. The nonlinear characteristics of manipulators are approximated using Koopman operator theory, yielding a ``global'' linear model. Additionally,   a virtual dynamics of force is added to the involved optimization problem, which represents the dynamic relationship between the end position and the contact force.  The terminal constraint set is derived by calculating the maximal robust positive invariant set of the linear system. Simulation results validate the effectiveness of the proposed control strategy, demonstrating its ability to achieve both high-precision path tracking and accurate force regulation for robotic manipulators.

Manipulators, path following, Koopman operator, model predictive control, terminal constraint set