Path Tracking in Cable Suspended Parallel Robots through Position- Dependent Model Predictive Control with Embedded Integrator

Abstract

This work proposes a novel Model Predictive Control (MPC) algorithm for Cable-Driven Robots (CDRs), with a suspended configuration, to achieve good performances in terms of trajectory tracking of the end-effector as well as ensuring the positiveness of cable tensions. A two-stage controller is exploited to handle model nonlinearities. Firstly, a position-dependent MPC algorithm with embedded integrator is designed to evaluate the optimal cable tensions that are required to track trajectory, while considering constraints on the feasible tensions. Secondly, the related motor torques are evaluated taking into account the dynamics of the electric motor themselves, through a dedicated feedforward approach. With the goal to assess the proposed control algorithm, a 3-dof cable suspended spatial robot is considered and different trajectory tracking tasks are performed: firstly, an unfeasible reference is tested in order to assess the control algorithm in the worstcase scenario and, secondly, two feasible and common trajectories are considered as reference laws of motion. Simulative outcomes are displayed and contour errors are reported to numerically evaluate the controller performances.