Alberto Pasetto

In this paper, the possibility of harvesting energy from the vibrations of a plate is analyzed. The harvester takes the form of a cantilever dynamic vibration absorber equipped with a piezoelectric layer and tuned by means of a tip mass to the first mode of vibration of the plate. A mathematical model of the coupled system composed of the plate and the harvester is presented. The validity of the proposed harvester is proved by means of simulations carried out with the modal expansions approach. Simulation results highlighting the effects of harvester tuning and location are presented as well. Then, the validity of the harvester is confirmed by experimental tests carried out both with a concentrated impulsive load and with a distributed pressure load. Simulations and experimental tests are performed on the cantilever piezoelectric dynamic vibration absorber and on the same piezoelectric layer directly bonded to the plate surface. Results show an improvement in terms of generated voltage when the proposed novel device is used in place of the simple layer.

The precise control of an aerial manipulator presents a formidable challenge due to the inherent mobility of its base, which is subject to both external disturbances and dynamic disturbances due to manipulator motions. In this paper, we introduce two Closed-Loop Inverse Kinematics (CLIK) control algorithms tailored to aerial manipulators. The first algorithm operates at the velocity level and uses the Generalized Jacobian for inverse kinematics, while the second one operates at the acceleration level. We evaluate their performance in a simulated environment, replicating real-world challenges such as the wind effect, sensors noise, uncertainty of the system inertial parameters, and impulsive forces at the end-effector. Trajectory tracking simulated experiments are carried out for a two- and three-degree-of-freedom (DOF) aerial manipulator tracking a circular trajectory with its end-effector. Both algorithms demonstrate promising results in coping with external disturbances and variations in the inertial parameters, enhancing the precision of the trajectory tracking control. The acceleration-level algorithm shows overall better performance compared to the velocity-level one in the face of greater implementation complexity and computational burden.