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Fast-response hot-wire flow sensors for wind and gust estimation on UAVs

ORAL

Abstract

Unsteady airflow phenomena such as wind gusts present a control challenge for Unmanned Aerial Vehicle (UAV) operations. The prevailing control strategy is to apply corrective action after setpoint error is detected. A proactive approach, enabling faster and more precise control, requires measuring the wind directly with onboard flow sensors. Existing anemometry techniques are unsuitable due to form factor, resolution, or robustness requirements. To overcome this, a novel, fast-response sensor to measure a wind vector in two dimensions is introduced. This sensor, named 'MAST' (MEMS Anemometry Sensing Tower), leverages advances in microelectromechanical (MEMS) hot-wire devices to produce a solid-state, lightweight, and robust flow sensor suitable for real-time wind estimation onboard a UAV. The MAST is a modular system that supports multiple configurations, which were evaluated in the wind tunnel. A neural network sensor model was trained to predict the direction (0-360 degrees) and magnitude (0-5 m/s) of the wind. Additionally, the bandwidth of the MAST system is sufficiently high to capture the relevant atmospheric phenomena. The resulting system stands to greatly enhance UAV wind estimation capabilities.

Presenters

  • Nathaniel Simon

    Princeton University

Authors

  • Nathaniel Simon

    Princeton University

  • Alexander Pique

    Princeton University

  • David Snyder

    Princeton University

  • Kyle Ikuma

    Princeton University

  • Anirudha Majumdar

    Princeton University

  • Marcus Hultmark

    Princeton University