Study of Synthetic Airspeed Algorithm Based on Machine Learning for Lift Coefficient Curve Fitting

Chen, Dianzhong and Xu, Yue and Wang, Lei (2020) Study of Synthetic Airspeed Algorithm Based on Machine Learning for Lift Coefficient Curve Fitting. In: Mobimedia 2020, 27-28 August 2020, Cyberspace.

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Abstract

Traditional air data system of airplane utilizes pitot probe for airspeed measurement. However, problems such as icing and bird strike will lead to failure of pitot probe. Airspeed display loss is rated as disastrous loss status. Airspeed calculation algorithm based on inertial data and movable surface positions (status of flaps and slats) has been studied by the Boeing Company and the Airbus Company and applied in airplane models of Boeing 787 and Airbus A350. Commercial Airplane of China has been dedicated in studying algorithm of airspeed calculation. Study indicates the importance of accurate lift coefficient identification for different flight configurations under certain attack angles. Theoretical analysis indicates the relationship of piecewise linearity between lift coefficient and attack angle. Based on the above relationship, machine learning algorithm of support vector regression (SVR) is applied to process air data. Furthermore, synthetic airspeed algorithm is proposed and verified.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: airspeed calculation algorithm support vector regression (svr)
Subjects: Q Science > QA Mathematics > QA76 Computer software
Depositing User: EAI Editor I.
Date Deposited: 04 Feb 2021 13:41
Last Modified: 04 Feb 2021 13:41
URI: https://eprints.eudl.eu/id/eprint/828

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