S. Nazarov, P.-O. Gutman

Atmospheric wind and turbulence significantly affect flight efficiency, control performance, and safety. This paper describes a new original in-flight algorithm for wind/turbulence field estimation using a standard unmanned rotorcraft sensor kit and control signals produced by the flight control system. A linear identified model is proposed as a basic model of helicopter dynamics. This model is modified into a quasi-nonlinear model by adding trim data and nonlinear kinematic equations. A nonlinear Unscented Kalman Filter is designed using the quasi-nonlinear model and the scaled unscented transformation to estimate wind components in the North-East-Down frame. The resulting estimate is split using moving averaging into the steady horizontal wind and atmospheric turbulence. This algorithm has been tested on a continuous model-stitched simulation in which the wind and atmospheric turbulence simulated by the Dryden model have been added. The result was also validated by an actual Steadicopter Black Eagle (BE-50) unmanned helicopter flight test.

49th European Rotorcraft Forum 2023, Bückeburg, 2023

Conference Paper

englisch

21,0 x 29,7 cm, 17 Seiten

DGLR-Bericht, 2023, 2023-01, 49th European Rotorcraft Forum 2023 - Proceedings; S.1-17; 2023; Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V., Bonn

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2023