Ricerc@Sapienza

This paper proposes a discrete-time linear parameter varying (LPV) unknown input observer (UIO) for the diagnosis of actuator faults and ice accretion in unmanned aerial vehicles (UAVs). The proposed approach, which is suited to an implementation on-board, exploits a complete 6-degrees of freedom (DOF) UAV model, which includes the coupled longitudinal/lateral dynamics and the impact of icing. The LPV formulation has the advantage of allowing the icing diagnosis scheme to be consistent with a wide range of operating conditions.

Aerial image mosaicking of an area of interest is the process of combining multiple images, of an area with overlapping regions, into a single comprehensive view. In this process, image registration, i.e., the operation of geometric transformation to align and overlay two or more images of the same scene taken from different viewpoints, starting from their common parts, plays a key role in terms of artifacts reduction. In the current state-of-the-art, image registration of aerial images is usually performed through the use of the homography transformation.

Unmanned aerial vehicles are characterized by a set of requirements, like high efficiency, resiliency, and reliability that conflict with the other main requirement of high power density aimed at minimizing the overall weight and size. This article proposes a novel, modular multiphase drive for a quadrotor drone, realized through the integration of an axial flux permanent magnet machine and a GaN-based power electronic converter. After an overview of the design process, starting from the propeller choice, a brief description of the system components is presented.