由于飞行过程中飞行环境与自身特性的大幅度变化,导弹的飞行动力学特性和结构模态参数变化范围很大,难以精确建模,对导弹的气动伺服弹性稳定性带来潜在危险,传统结构滤波器的适用性也难以保证。提出一种自适应结构滤波器的设计方法,利用导弹输入指令和传感器输出的采样信号,建立导弹的自回归滑动平均(ARMA)模型;采用递归最小二乘算法,在线辨识飞行器的结构模态参数并用于实时更新滤波器的中心频率。仿真结果表明:相对于传统设计方法,自适应结构滤波器在较大参数摄动范围内都可明显提高导弹的气动伺服弹性稳定裕度,对于导弹飞行环境和结构特性的变化都有较强的鲁棒性。

Because of the existence of significant variation of the environment and vehicle characteristics during the flight of missiles, the flight dynamic characteristics and the structure modal parameters of missiles also vary in a wide range, thus making it hard to model the system accurately. This brings potential danger to the aeroservoelastic stability of missiles. Conventional structure filters are often unsuitable for use. This article presents a new design method of adaptive structure filters for missiles. Sample signals of input command and sensor output are utilized to establish the autoregressive moving average (ARMA) model of missiles. By applying the recursive least square method, realtime structure modal parameters of missiles are identified and utilized to update the central frequency of structure filter. Simulation results indicate that, compared with the conventional structure filter, the adaptive structure filter can increase the stability margin of missiles significantly in the case of wide-range parameter perturbations, and that it is robust with regard to changes in flight environment and structure characteristics.