Speaker
Description
Within the framework of the technological development activities associated with the RFX-mod2 experimental infrastructure and carried out in the context of the NEFERTARI project, a research activity was conducted focusing on motion planning and control of the robotic manipulator intended to perform remote handling operations. These developments are part of a broader program aimed at upgrading the technological infrastructure of the RFX facility in order to improve operational reliability and enhance experimental capabilities in the field of nuclear fusion research.
After updating the remote handling system with a novel kinematic model and therefore improving its dexterity in the operational workspace, based on this model a motion planning procedure is developed to generate desired end-effector trajectories that are consistent with the operational environment. The desired trajectories defined in Cartesian space are subsequently transformed into reference signals in joint space thanks to an inverse kinematic approach, thus obtaining the position profiles required for the electric actuators installed in the various joints of the manipulator.
In order to guarantee accurate tracking of the reference signals, dedicated controllers are designed for each individual motor, while explicitly considering the dynamics of the actuation system. In this context, a robustness metric is explicitly incorporated into the control design process, with the aim of ensuring satisfactory performance even in the presence of model uncertainties and unmodeled contributions, such as unknown external disturbances.
The performance of the entire closed-loop system is numerically verified. In particular, the robustness of the control system is further assessed by applying a disk margin approach; this analysis allows a quantitative evaluation of the system tolerance with respect to simultaneous gain and phase variations. The results highlight the capability of the proposed control architecture to guarantee stable and robust performance under the expected operating conditions.