Title | Large Angle of Attack Prediction for Tail-Sitter Using ANN-Based Flush Air Data Sensing |
Author | |
Corresponding Author | Shan,Xiaowen |
DOI | |
Publication Years | 2023
|
ISSN | 1876-1100
|
EISSN | 1876-1119
|
Source Title | |
Volume | 845 LNEE
|
Pages | 6722-6731
|
Abstract | Flush air data sensing systems (FADS) have been widely applied on aerial vehicles to provide air data estimation. Air data such as angle of attack (AoA) and air speed can be estimated through resolving pressure measurements of the sensor matrix. These parameters can be utilized to improve the performance of flight control system and realize better flight performance. Existing FADS studies and applications can estimate AoA in the range typically below 55 . It is suitable for traditional fixed wing unmanned aerial vehicles (UAVs), but some fixed wing vertical take off and landing (VTOL) UAVs have requirements in measuring air data under larger AoA. In this work, a FADS based on artificial neural network has been applied on a tail-sitter to provided large AoA estimation in low Reynolds number. Computational fluid dynamic analysis has been carried out to evaluate the critical AoA where stall region affects the sensor matrix. Wind tunnel tests have been further carried to collect data for network training. The trained network can provide estimation of large AoA at the range of −80 to 80 with acceptable accuracy. |
Keywords | |
SUSTech Authorship | First
; Corresponding
|
Language | English
|
URL | [Source Record] |
Scopus EID | 2-s2.0-85151130293
|
Data Source | Scopus
|
Citation statistics |
Cited Times [WOS]:0
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Document Type | Conference paper |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/524283 |
Department | Department of Mechanics and Aerospace Engineering 前沿与交叉科学研究院 |
Affiliation | 1.Department of Mechanics and Aerospace Engineering,Southern University of Science and Technology,Shenzhen,518055,China 2.Academy for Advanced Interdisciplinary Studies,Southern University of Science and Technology,Shenzhen,518055,China |
First Author Affilication | Department of Mechanics and Aerospace Engineering |
Corresponding Author Affilication | Department of Mechanics and Aerospace Engineering |
First Author's First Affilication | Department of Mechanics and Aerospace Engineering |
Recommended Citation GB/T 7714 |
Tianchun,L. Y.,Li,Xiaoda,Wu,Yongliang,et al. Large Angle of Attack Prediction for Tail-Sitter Using ANN-Based Flush Air Data Sensing[C],2023:6722-6731.
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