基于SOKID的无人动力伞模型辨识

Model Identification of Unmanned Powered Parafoil Based on Subspace Observer/Kalman Filter Identification

对具有独特飞行特性的无人动力伞(Unmanned Powered Parafoil,UPP)进行了研究,建立了无人动力伞九自由度非线性动力学方程,研究了观测器/卡尔曼滤波辨识算法和改进的子空间观测器/卡尔曼滤波辨识算法。根据系统的飞行数据,辨识得到系统的纵向状态空间模型,分析了两种辨识模型的俯仰角响应特性和辨识精度。仿真结果表明子空间观测器/卡尔曼滤波辨识算法的一致和有效估计,能有效辨识无人动力伞的纵向动态模型。

Unmanned Powered Parafoil（UPP） of special flight characteristics is studied, and establish a 9-DOF nonlinear dynamic equation. A observer/kalman filter identification （OKID） method and advanced subspace observer/kalman filter identification （OKID） is researched. Using the flight data, the longitudinal state space models of UPP is identified and derived, and the identified model pitch angle response characters and identified precision are also analysed. The consistent and effective of the identification method are verified in a simulation experiment, and the validity of the identified longitudinal model is also tested in the fly.