Using Pose-Dependent Model Predictive Control for Path Tracking with Bounded Tensions in a 3-DOF Spatial Cable Suspended Parallel Robot

Abstract

This paper proposes the preliminary results on a novel control architecture based on model predictive control (MPC) for cable-driven parallel robots (CDPRs) and applies them to a three degrees of freedom (3-DOF) robot with a suspended configuration, leading to a cable-suspended parallel robot (CSPR). The goal of the control scheme is ensuring accurate path tracking of the reference end-effector path, while imposing a priori positive cable tensions. To handle the nonlinearities characterizing the dynamic model that governs this kind of multibody system and to keep the computational effort low, a position-dependent MPC algorithm with an embedded integrator is designed to compute the optimal cable tensions required to track the end-effector commanded path. Such tensions must belong to the feasible domain defined through a lower bound, which is slightly greater than zero, to ensure that cables pull the end-effector, and an upper bound, to represent the maximum stress that cables can withstand without breaking. The resulting controller is nonlinear, although it performs a local linearization in the prediction at each time step to reduce the computational effort. The optimal tensions are then transformed into the commanded motor torques through the inverse dynamic model of the servomotors driving the winches, since no force measurement is adopted in the controller implementation. The control architecture is designed and numerically validated through a spatial CSPR with lumped end-effector, and driven by three cables (i.e., with a non-redundant configuration). Four different paths are assumed to highlight various features of the proposed controller.