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Online System Identification of Unmanned Aerial Vehicle in Upset condition

机译:无人驾驶空中车辆在镦劲条件下的在线系统识别

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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.
机译:在文献中的在线系统识别(ID)方法中,在镦粗条件下,少数方法已知并在真正的飞机上验证了令人满意的条件,例如在线系统识别(ID)方法。这项工作考虑了古典系统ID方法的一些改进,以更好地适用于时变空气动力学系数的实时估计。该方法已经在模型飞机的实际飞行数据上进行了测试,以表达其有效性。

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