6533b7dcfe1ef96bd1272b97

RESEARCH PRODUCT

Wind component estimation for UAS flying in turbulent air

Fernando MontanoCaterina Grillo

subject

0209 industrial biotechnologyTurbulenceComputer scienceAuto-tuningWind estimationSettore ING-IND/03 - Meccanica Del VoloAerospace EngineeringScale (descriptive set theory)02 engineering and technology01 natural sciences010305 fluids & plasmasPower (physics)Data setExtended Kalman filterIdentification (information)020901 industrial engineering & automationEKFControl theory0103 physical sciencesWind componentUASFocus (optics)

description

One of the most important problem of autonomous flight for UAS is the wind identification, especially for small scale vehicles. This research focusses on an identification methodology based on the Extended Kalman Filter (EKF). In particular authors focus their attention on.the filter tuning problem. The proposed procedure requires low computational power, so it is very useful for UAS. Besides it allows a robust wind component identification even when, as it is usually, the measurement data set is affected by noticeable noises. (C) 2019 Elsevier Masson SAS. All rights reserved.

yearjournalcountryeditionlanguage
2019-10-01Aerospace Science and Technology
https://doi.org/10.1016/j.ast.2019.105317