Implementation of a 3-DOF Parallel Robot Adaptive Motion Controller

For fast and accurate motion of a Parallel Manipulator, model-based control needs to be implemented. In general in a model-based controller, exact knowledge of the system dynamics is required. However, the dynamic model has uncertainties not only because of the unmodeled dynamics but also when, for instance, unknown inertial parameters can appear. This kind of uncertainty limits the applicability of model-based controllers. To relax the requirement of exact knowledge, an adaptive controller has been developed. The controller is implemented in a modular way using Orocos, a real-time middleware. The proposed controller is compared with a fixed model passivity-based controller. Both control strategies are tested on a virtual and an actual prototype. From the simulations and experiments, the adaptive controller does not present a loss of accuracy when compared with the fixed controller; moreover, when a payload is handled by the robot, the results show that the adaptive controller improves the trajectory tracking precision.