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

Redundant actuated parallel robot is a multi-input and multi-output (MIMO) system which usually works in an uncertain environment. In this paper, the force/position hybrid control structure of 6PUS-UPU redundant actuation parallel robot is designed, and proportional–integral (PI) and model predictive control (MPC) cascade control strategies are used in the redundant branch of 6PUS-UPU redundant actuation parallel robot. The MPC algorithm is used in the current loop of the permanent magnet synchronous motor (PMSM) to restrain the motor parameter uncertainty and external disturbances influence on motor control. The MATLAB/ADAMS joint simulation method based on virtual 6PUS-UPU redundant actuation parallel robot prototype is used to test the performance of the proposed control strategy. The performance of proposed PI-MPC control strategy is compared with the traditional PI–PI control strategy. The simulation results show that the MPC controller can improve the tracking ability of the motor torque, guarantee the system robustness under the parameter variations and load disturbance environment. •Parallel robot is designed by force/position hybrid control structure.•The model predictive control algorithm is applied to the parallel robot control.•The algorithm can significantly improve the robustness of the robot.•The influence of robot model mismatch and the uncertain disturbance is suppressed.