为准确描述过失速机动中非定常气动力特性,研究了以非线性微分方程为基本结构的非定常气动建模方法。基于动力学系统建模思想,分析揭示该模型的物理机理,并发展和改进了基于风洞强迫振荡试验的模型参数辨识方法:基于小振幅试验数据,采用线性回归参数辨识方法辨识确定气动模型中特征时间常数等线性参数;基于大振幅试验数据,采用遗传算法全局寻优辨识气动模型中非线性项参数。以带中心体三角翼模型为例进行气动建模与验证,研究结果表明:模型可精确预测不同机动下非定常气动特性;建模方法具有较强的工程可行性。

In order to describe the unsteady aerodynamic characteristics of an aircraft in post-stall maneuvering, this article studies the unsteady aerodynamic modeling in the form of nonlinear differential equations. In view of its physical mechanism based on dynamic system modeling, the identification method using data from forced oscillation wind tunnel test is investigated. Based on data from small-amplitude experiments, the linear regression method is used to find the linear parameters such as the time constants, while genetic algorithm is used to identify the nonlinear correction terms based on data from large-amplitude experiments. Wind tunnel test with a model delta wing plus a center body are used to verify this method. The result shows that the model is able to predict the unsteady aerodynamic loads accurately in different movements, which bears proof on the practicality of the flight dynamic analysis.