Model Predictive Control for a 3-DoF Suspended Cable Robot Based on Laguerre Functions

Taking advantages of Laguerre functions, this paper addresses model predictive control for a 3 degrees of freedom suspended parallel cable robot. The parallel structure and using cables in this class of robots introduce new challenges. The major challenge is to maintain the tensile force of the cables in all robot maneuvers. While in many control approaches, positive tension distribution of the cables is performed by a separate optimization algorithm, in MPC, the related constraints can be considered directly in the control problem. However, reducing the computational load is a crucial challenge in MPC for real-time implementation. For this goal, in this study, Laguerre functions are employed to model the control trajectories, and also Hildreth’s quadratic programming is proposed to solve the optimal control problem in the presence of constraints. The proposed control scheme is applied to a 3 DoF suspended CDPR, and the performance of the proposed control algorithm is compared with linear model predictive control. The simulation results demonstrate that the recommended control scheme presents an effective performance in tracking while considering tensile constraints besides reducing the computational load.