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Online System Identification of Unmanned Aerial Vehicle in Upset condition
- Authors
- Seo, Gwang-gyo; Kim, Yoonsoo
- Issue Date
- Oct-2018
- Publisher
- IEEE
- Keywords
- Online System Identification; Non-linear System Parameter Identification; UAV; Regression; Upset condition
- Citation
- 2018 18TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS), pp 348 - 350
- Pages
- 3
- Indexed
- SCOPUS
- Journal Title
- 2018 18TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS)
- Start Page
- 348
- End Page
- 350
- ISSN
- 2093-7121
- Abstract
- Few methods have been known and validated on real aircraft in upset condition such as stall or spin for online system identification (ID) methods in the literature. This work considers some improvement of classical system ID methods to be better suited for the real-time estimation of time-varying aerodynamic coefficients. The proposed method has been tested on real flight data of a model aircraft to show its effectiveness.
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