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为了确保机翼损伤后飞机的飞行安全,提出了一种在线的故障诊断方法.首先,根据输入输出特性,采用遗忘因子递推最小二乘法对飞机故障后的气动导数进行辨识,建立了机翼损伤故障的数学模型;然后,结合多模型方法和中心差分卡尔曼滤波器(central difference Kalman filter,CDKF)各自的优点,实现对机翼损伤的故障诊断,并采用强跟踪滤波器在线更新CDKF的采样点,以增强CDKF的自适应能力.最后,通过仿真结果验证了本文所提方法的有效性.
In order to ensure the flight safety of aircrafts after wing damage, an online fault diagnosis method is proposed.Firstly, based on the input and output characteristics, the forgetting factor recursive least squares method is used to identify the aerodynamic derivatives after aircraft failure, and the wing Then, combining the advantages of multi-model method and central difference Kalman filter (CDKF), fault diagnosis of wing damage can be realized and a strong tracking filter can be used to update CDKF Sampling points to enhance the self-adaptive ability of CDKF.Finally, the simulation results verify the effectiveness of the proposed method.