Title :
Surface wind profile measurement using multiple small unmanned aerial vehicles
Author :
Haiyang Chao ; YangQuan Chen
Author_Institution :
Dept. of Electr. & Comput. Eng., Utah State Univ., Logan, UT, USA
fDate :
June 30 2010-July 2 2010
Abstract :
This paper focuses on using multiple unmanned aerial vehicles (UAVs) for measurement and estimation of the mesoscale or microscale wind field. Low-level wind and near-surface wind could have many applications such as wind power harvesting, weather prediction, pollution dispersion, and safer aircraft landing/take-off, etc. However, current wind profiling techniques like balloons and meteorological towers are not only expensive but also inflexible. UAVs could be used to measure the wind strength and directions at a flexible position and altitude in real time. Moreover, groups of UAVs with a certain formation could measure the vertical or horizon wind profiling simultaneously. Given the measurements of an area, the wind field could be approximately modeled by a series of partial differential equations (PDEs). An incremental parameter estimation algorithm using single and multiple UAVs is developed. Preliminary simulation and experimental results show the effectiveness of the proposed method.
Keywords :
atmospheric boundary layer; atmospheric measuring apparatus; atmospheric techniques; partial differential equations; remotely operated vehicles; wind; aircraft landing; aircraft take-off; balloons; incremental parameter estimation algorithm; mesoscale wind field; meteorological towers; microscale wind field; multiple small unmanned aerial vehicles; near-surface wind; partial differential equations; pollution dispersion; surface wind profile measurement; weather prediction; wind power harvesting; wind strength; Aircraft; Land pollution; Meteorology; Poles and towers; Pollution measurement; Surface contamination; Unmanned aerial vehicles; Weather forecasting; Wind energy; Wind forecasting;
Conference_Titel :
American Control Conference (ACC), 2010
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-7426-4
DOI :
10.1109/ACC.2010.5530609