TY - GEN
T1 - Wind Estimation for Multirotor UAV Control based on Surface Pressure Distribution
AU - Yu, Junhao
AU - Chou, Wusheng
AU - Rong, Yongfeng
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The multirotor unmanned aerial vehicles (UAVs) are currently commonly used for various outdoor operations; However, gusts of wind may affect their stable control, and even lead to safety accidents. The common approach is to install wind sensors to obtain wind information for gust-resistant control, but traditional sensors are large, heavy, and slow to respond, making them unsuitable for small UAVs. In this paper, a compact, lightweight, fast-responsive wind estimation module is designed. When wind passes over the module, the surface pressure distribution information will be captured by the pressure sensors, and an artificial neural network is proposed to estimate the wind speed and direction. The effectiveness of the module was verified by testing it on a small UAV in the 5m/s wind field, achieving 4.09° direction estimation error and 0.34m/s speed estimation error.
AB - The multirotor unmanned aerial vehicles (UAVs) are currently commonly used for various outdoor operations; However, gusts of wind may affect their stable control, and even lead to safety accidents. The common approach is to install wind sensors to obtain wind information for gust-resistant control, but traditional sensors are large, heavy, and slow to respond, making them unsuitable for small UAVs. In this paper, a compact, lightweight, fast-responsive wind estimation module is designed. When wind passes over the module, the surface pressure distribution information will be captured by the pressure sensors, and an artificial neural network is proposed to estimate the wind speed and direction. The effectiveness of the module was verified by testing it on a small UAV in the 5m/s wind field, achieving 4.09° direction estimation error and 0.34m/s speed estimation error.
KW - artificial neural network
KW - pressure distribution
KW - wind estimation
UR - https://www.scopus.com/pages/publications/85206107404
U2 - 10.1109/ICECAI62591.2024.10674795
DO - 10.1109/ICECAI62591.2024.10674795
M3 - 会议稿件
AN - SCOPUS:85206107404
T3 - 2024 5th International Conference on Electronic Communication and Artificial Intelligence, ICECAI 2024
SP - 494
EP - 499
BT - 2024 5th International Conference on Electronic Communication and Artificial Intelligence, ICECAI 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Electronic Communication and Artificial Intelligence, ICECAI 2024
Y2 - 31 May 2024 through 2 June 2024
ER -