基于递推傅里叶变换的飞行器参数在线辨识方法

在线辨识在现代飞行控制系统设计中扮演越来越重要的角色，飞行器模型的在线更新使得人们可以采用更智能的控制方法。基于计算精度和速度的考虑，在线辨识方法通常以递推方式进行，主要分为时域和频域两大类方法。在建立飞行器系统模型结构的基础上，利用频域递推傅里叶变换及最小二乘方法，实现对气动及控制偏导数的在线辨识。针对某飞机纵向通道的在线辨识仿真验证该方法有效，且计算速度和收敛速度快，辨识结果与参数真实值之间的一致性好，方法对传感器噪声有较强的适应性。最后，分析比较了各种典型激励信号对辨识结果的影响，为进行实际在线辨识试验提供了参考依据。

Online Aircraft Parameter Identification Using Recursive Fourier Transform

Online identification plays a more and more important role in aircraft control system design. Real-time aircraft model updating will allow more intelligent control methods to be adopted. For consideration of velocity and precision of computation, online identification is generally carried on recursively and can be divided into two categories: time-domain methods and frequency-domain methods. Based on the modeling of an aircraft system, the recursive Fourier transform and least square methods are performed in this paper to identify the aerodynamic derivatives and control derivatives online. The approach is validated by simulation of an aircraft's longitudinal model, whose computation and convergence velocities are both fast. The result shows that the identified parameters agree well with the true values, and the algorithm has high adaptability to sensor noise. Finally, the influence of different input signals on identification are investigated, which can serve as reference in real flight identification.