Abstract

In this study, identification of nonlinear aerodynamic systems based on an improved nonlinear state-space modeling approach is presented to predict transonic aeroelastic behaviors of aircraft structures. It starts with identifying a linear state-space aerodynamic model by using the eigensystem realization algorithm and observer/Kalman filter identification methods. Subsequently, the remaining parameters of the nonlinear state-space aerodynamic model are determined through an output error-minimization procedure, based on a new training data generation methodology. To illustrate the approach, two- and three-dimensional transonic aeroelastic configurations are studied. The transonic aeroelastic behaviors predicted via the proposed approach agree well with those obtained via computational fluid dynamics technique in the interested range of dynamic pressure.

中文翻译：

---

非线性气动系统的辨识及其在飞机结构跨音速气动弹性中的应用

摘要

在这项研究中，提出了一种基于改进的非线性状态空间建模方法的非线性空气动力系统识别方法，以预测飞机结构的跨音速空气弹性行为。首先使用特征系统实现算法和观察者/卡尔曼滤波器识别方法识别线性状态空间空气动力学模型。随后，基于新的训练数据生成方法，通过输出误差最小化过程确定非线性状态空间空气动力学模型的其余参数。为了说明这种方法，研究了二维和三维跨音速气动弹性构型。