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Statistical methods for launch vehicle guidance, navigation, and control (GN&C) system design and analysis.

机译：用于运载火箭制导，导航和控制（GN＆C）系统设计和分析的统计方法。

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摘要

A novel trajectory and attitude control and navigation analysis tool for powered ascent is developed. The tool is capable of rapid trade-space analysis and is designed to ultimately reduce turnaround time for launch vehicle design, mission planning, and redesign work. It is streamlined to quickly determine trajectory and attitude control dispersions, propellant dispersions, orbit insertion dispersions, and navigation errors and their sensitivities to sensor errors, actuator execution uncertainties, and random disturbances.;The tool is developed by applying both Monte Carlo and linear covariance analysis techniques to a closed-loop, launch vehicle guidance, navigation, and control (GN&C) system. The nonlinear dynamics and flight GN&C software models of a closed-loop, six-degree-of-freedom (6-DOF), Monte Carlo simulation are formulated and developed. The nominal reference trajectory (NRT) for the proposed lunar ascent trajectory is defined and generated. The Monte Carlo truth models and GN&C algorithms are linearized about the NRT, the linear covariance equations are formulated, and the linear covariance simulation is developed.;The performance of the launch vehicle GN&C system is evaluated using both Monte Carlo and linear covariance techniques and their trajectory and attitude control dispersion, propellant dispersion, orbit insertion dispersion, and navigation error results are validated and compared. Statistical results from linear covariance analysis are generally within 10% of Monte Carlo results, and in most cases the differences are less than 5%. This is an excellent result given the many complex nonlinearities that are embedded in the ascent GN&C problem. Moreover, the real value of this tool lies in its speed, where the linear covariance simulation is 1036.62 times faster than the Monte Carlo simulation. Although the application and results presented are for a lunar, single-stage-to-orbit (SSTO), ascent vehicle, the tools, techniques, and mathematical formulations that are discussed are applicable to ascent on Earth or other planets as well as other rocket-powered systems such as sounding rockets and ballistic missiles.
机译：开发了一种新型的动力上升轨迹和姿态控制及导航分析工具。该工具能够进行快速的贸易空间分析，旨在最终减少运载火箭设计，任务计划和重新设计工作的周转时间。它可以简化以快速确定轨迹和姿态控制偏差，推进剂偏差，轨道插入偏差以及导航误差及其对传感器误差，执行器执行不确定性和随机干扰的敏感性。该工具是通过同时应用蒙特卡洛和线性协方差开发的闭环，运载火箭制导，导航和控制（GN＆C）系统的分析技术。制定并开发了闭环，六自由度（6-DOF）的非线性动力学和飞行GN＆C软件模型，蒙特卡洛模拟。定义并生成了拟议的月球上升轨迹的名义参考轨迹（NRT）。对NRT进行了蒙特卡罗真实模型和GN＆C算法的线性化，建立了线性协方差方程，并开发了线性协方差仿真。;使用蒙特卡洛和线性协方差技术评估了运载火箭GN＆C系统的性能验证并比较了轨迹和姿态控制色散，推进剂色散，轨道插入色散以及导航误差结果。线性协方差分析的统计结果通常在蒙特卡洛结果的10％以内，并且在大多数情况下，差异小于5％。考虑到GN＆C上升问题中嵌入了许多复杂的非线性，这是一个极好的结果。此外，该工具的真正价值在于它的速度，线性协方差仿真的速度比蒙特卡洛仿真快1036.62倍。尽管给出的应用和结果适用于月球，单阶段入轨（SSTO），上升飞行器，但所讨论的工具，技术和数学公式适用于地球或其他行星以及其他火箭的上升动力系统，例如探空火箭和弹道导弹。

著录项

  • 作者

    Rose, Michael Benjamin.;

  • 作者单位

    Utah State University.;

  • 授予单位 Utah State University.;
  • 学科 Engineering Aerospace.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 230 p.
  • 总页数 230
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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