Real-time path-tracking control of robotic manipulators with bounded torques and torque-derivatives

Minimum-time path-tracking control of robotic manipulators assumes a relevant role in industrial applications where efficiency is an issue. On the other hand, minimizing the traveling time leads to an increment of the mechanical solicitations: the actuators dynamic limits can be easily exceeded. For this reasons, kinematic and/or dynamic constraints are normally taken into account when planning optimal trajectories through off-line algorithms. Nevertheless this precaution, dynamic limits can be easily violated during actual operations due to model uncertainties and the action of the feedback controller. In order to fulfill with certainty the given constraints, planned trajectories are typically online scaled by means of dynamic filters. Normally, this is done by only considering torque constraints. On the contrary, in this paper, the trajectory is online scaled by also taking into account the existence of bounds on the torque derivatives. Indeed, torque derivatives have a direct impact both on the mechanical solicitations and on the tracking accuracy. A new nonlinear filter is proposed for the optimal trajectory scaling. Its effectiveness is verified by means of simulations.