基于实际飞行数据的包含惯性参数和力-力矩关系的飞机非线性动力学模型辨识

Lorand Lukacs, B. Lantos
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引用次数: 0

摘要

本文的主要内容是飞机非线性动力学模型及其惯性参数(质心和惯性矩阵)的辨识。假定飞机没有内置导航系统,也没有安装在控制面上的任何传感器。飞机的飞行受到飞行员操纵的操纵杆和踏板的影响,而这些操纵杆和踏板的位置只能通过视觉观察到。在数据记录时,在飞机上部署了外部传感系统(GPS、IMU)和摄像系统,支持飞行数据的收集,用于状态估计和模型识别。先前的文章讨论了执行器信号的计算和状态估计。本文主要研究了当感知信息在与飞机几何选择的框架平行的框架中可用时,如何识别未知的COG和惯性矩阵以及力-扭矩模型。力-力矩模型是在刚体动力学方程的基础上,附加三维力和力矩的加权非线性项。从物理角度选择非线性控制函数,利用奇异值分解技术确定非线性控制函数的参数。从惯性参数中只知道质量。考虑了风的影响。通过约束全局搜索,选择合适的目标函数,计算惯性参数。以滑翔机为例,给出了实际飞行数据的计算结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nonlinear dynamic model identification of airplanes including inertial parameters and force-torque relations based on real flight data
The primary scope of the paper lies on the identification of an aircraft's nonlinear dynamic model together with the inertial parameters (center of mass and inertia matrix). It is assumed that the aircraft has no inbuilt navigational system, nor any sensors mounted on its control surfaces. The flight of the airplane is influenced by the control column and pedals manipulated by the pilot whose positions can only be observed visually. For the time of data logging, an external sensory system (GPS, IMU) and a camera system were deployed on the airplane supporting the collection of flight data for state estimation and model identification. An earlier paper discussed the computation of the actuator signals and the state estimation. The present paper concentrates on the identification of the unknown COG and inertia matrix together with the force-torque model if the sensory information is available in a frame parallel with the geometrically chosen frame of the airplane. The force-torque model is based on the dynamical equations of rigid body with additional weighted nonlinear terms for 3D forces and torques. Dominating nonlinear functions are selected by physical considerations and their parameters are determined using SVD technique. From the inertial parameters only the mass is known. Wind effects are taken into consideration. Inertial parameters are computed by constrained global search based on an appropriately chosen objective function. The results are presented for a sailplane using real flight data.
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