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A method to predict the orbital lifetimes of free tethers and tether-trailing satellites using artificial neural networks.

机译:一种使用人工神经网络预测自由系链和系链跟踪卫星的轨道寿命的方法。

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摘要

his dissertation deals with the development of a method to predict the orbital lifetimes of uncontrolled free tethers and tether-trailing satellites originating in low-to-moderate altitude Earth orbits. The problem is solved by application of the "empirical method." Two mathematical models to simulate the orbital evolution of tethered systems are developed. In both models the system is discretized into a series of interconnected point masses, orbiting an oblate Earth and transiting an oblate, rotating, temporally and globally averaged atmosphere. For aerodynamic drag calculations, tether segments are modeled as right circular cylinders, and any end-body is modeled as a sphere. Drag coefficients vary as a function of shape and Knudsen number. In the "multibody model", connections between masses are elastic, and the system is free to assume any orientation. Newtonian equations of motion are numerically integrated. In the "orbital element propagation model", connections between masses are inelastic, and the system is constrained to remain aligned along the local vertical. Gauss' form of Lagrange's Planetary Equations, in terms of equinoctial elements, are used to propagate the orbital elements describing the orbit of the system's center of mass. The element propagation model is shown to provide, for initially unstretched systems aligned along the local vertical, accurate results, very quickly, as compared to those obtained using the multibody model. An algorithm to train feed-forward artificial neural networks, by minimizing the sum of the squares of percent errors, is derived and shown to be invaluable in training networks to represent widely-spread real-valued data. A hybrid training approach, using the derived algorithm in conjunction with the standard backpropagation training algorithm, is described and demonstrated. This approach often reduces network training time, and it is used to train three networks with lifetime data provided by the element propagation model: one to predict the orbital lifetimes of free tethers, one to predict lifetimes of upward-deployed subsatellites trailing a tether, and one to provide correction factors that account for the effects of initial orbit inclination and argument of latitude. The accuracies of network-predicted lifetimes, as compared to those obtained using the multibody model, are demonstrated in 90 cases with randomly chosen initial conditions and system physical dimensions. In all cases, the network's results are shown to be accurate to within
机译:他的论文涉及一种方法的开发,该方法可以预测源自中低高度地球轨道的不受控制的自由系绳和系绳拖曳卫星的轨道寿命。通过应用“经验方法”可以解决该问题。开发了两个数学模型来模拟系留系统的轨道演化。在这两个模型中,系统都离散为一系列相互连接的点质量,它们绕着扁圆的地球运行并经过扁圆的,旋转的,时间上和全球平均的大气。对于气动阻力计算,将系链段建模为直圆柱体,并将任何端体建模为球体。阻力系数随形状和克努森数的变化而变化。在“多体模型”中,质量之间的连接是弹性的,并且系统可以自由地采取任何方向。牛顿运动方程是数值积分的。在“轨道元素传播模型”中,质量之间的连接是非弹性的,并且系统被约束为沿局部垂直方向保持对齐。用等量元素表示的高斯形式的拉格朗日行星方程式用于传播描述系统质心轨道的轨道元素。与使用多实体模型获得的结果相比,元素传播模型显示出可以为最初未拉伸的系统沿局部垂直方向对齐提供非常准确的结果。通过最小化误差百分比的平方和,得出了一种用于训练前馈人工神经网络的算法,该算法在代表广泛分布的实值数据的训练网络中具有不可估量的价值。描述和演示了一种混合训练方法,它将派生算法与标准反向传播训练算法结合使用。这种方法通常会减少网络训练时间,并且用于通过元素传播模型提供的寿命数据来训练三个网络:一种方法用于预测自由系链的轨道寿命,一种方法用于预测在系链后向上部署的子卫星的寿命,以及一种提供校正因子,这些校正因子说明了初始轨道倾角和纬度的影响。与使用多体模型获得的寿命相比,网络预测的寿命精度在90例随机选择的初始条件和系统物理尺寸的情况下得到了证明。在所有情况下,网络结果均显示在

著录项

  • 作者

    Warnock, Ted Wesley.;

  • 作者单位

    Auburn University.;

  • 授予单位 Auburn University.;
  • 学科 Aerospace engineering.;Computer science.;Mechanics.
  • 学位 Ph.D.
  • 年度 1992
  • 页码 260 p.
  • 总页数 260
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:50:14

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