期刊
AEROSPACE SCIENCE AND TECHNOLOGY
卷 89, 期 -, 页码 307-317出版社
ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
DOI: 10.1016/j.ast.2019.04.012
关键词
Online system identification; Fixed-wing aircraft; Upset condition; Least-squares method; Unscented Kalman filter
资金
- National Research Foundation of Korea (NRF) - Ministry of Science and ICT [NRF-2017R1A5A1015311]
Online system identification became an integral part of the design process for aerodynamic parameter estimation with the technological progress. This paper presents two Kalman-filter based online system identification (SID) techniques for estimating aerodynamic parameters of fixed-wing aircraft in upset condition like stall. Unlike existing SID ones, the proposed methods first include aerodynamic characteristics directly in the aircraft dynamics, i.e. variation of aerodynamic derivatives or flow separation point, associated with the upset condition. Then, the conventional or unscented Kalman filter is applied in real time to obtain optimal estimates of the aerodynamic parameters under consideration. The proposed methods are tested with real flight data sets of several aircraft to demonstrate their effectiveness and superiority to a recently proposed method. (C) 2019 Elsevier Masson SAS. All rights reserved.
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