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Multidisciplinary Optimization Approach for Design and Operation of Constrained and Complex-shaped Space Systems.

机译：约束复杂形状空间系统设计与运行的多学科优化方法。

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摘要

The design of a small satellite is challenging since they are constrained by mass, volume, and power. To mitigate these constraint effects, designers adopt deployable configurations on the spacecraft that result in an interesting and difficult optimization problem. The resulting optimization problem is challenging due to the computational complexity caused by the large number of design variables and the model complexity created by the deployables. Adding to these complexities, there is a lack of integration of the design optimization systems into operational optimization, and the utility maximization of spacecraft in orbit.;The developed methodology enables satellite Multidisciplinary Design Optimization (MDO) that is extendable to on-orbit operation. Optimization of on-orbit operations is possible with MDO since the model predictive controller developed in this dissertation guarantees the achievement of the on-ground design behavior in orbit. To enable the design optimization of highly constrained and complex-shaped space systems, the spherical coordinate analysis technique, called the "Attitude Sphere", is extended and merged with an additional engineering tools like OpenGL. OpenGL's graphic acceleration facilitates the accurate estimation of the shadow-degraded photovoltaic cell area. This technique is applied to the design optimization of the satellite Electric Power System (EPS) and the design result shows that the amount of photovoltaic power generation can be increased more than 9%. Based on this initial methodology, the goal of this effort is extended from Single Discipline Optimization to Multidisciplinary Optimization, which includes the design and also operation of the EPS, Attitude Determination and Control System (ADCS), and communication system.;The geometry optimization satisfies the conditions of the ground development phase; however, the operation optimization may not be as successful as expected in orbit due to disturbances. To address this issue, for the ADCS operations, controllers based on Model Predictive Control that are effective for constraint handling were developed and implemented. All the suggested design and operation methodologies are applied to a mission "CADRE", which is space weather mission scheduled for operation in 2016. This application demonstrates the usefulness and capability of the methodology to enhance CADRE's capabilities, and its ability to be applied to a variety of missions.
机译：小卫星的设计具有挑战性，因为它们受到质量，体积和功率的限制。为了减轻这些约束效应，设计人员在航天器上采用了可部署的配置，这导致了有趣且困难的优化问题。由于大量设计变量和可部署对象创建的模型复杂性导致的计算复杂性，最终的优化问题具有挑战性。除了增加这些复杂性之外，还缺乏将设计优化系统集成到运行优化中以及将航天器在轨道上的效用最大化的能力。先进的方法论使得卫星多学科设计优化（MDO）可以扩展到在轨运行。 MDO可以优化在轨运行，因为本文开发的模型预测控制器保证了在轨实地设计行为的实现。为了优化高度受限和复杂形状的空间系统的设计，扩展了称为“姿态球”的球坐标分析技术，并与诸如OpenGL的其他工程工具合并。 OpenGL的图形加速功能有助于准确估计阴影退化的光伏电池区域。将该技术应用于卫星电力系统（EPS）的设计优化，设计结果表明，光伏发电量可以增加9％以上。基于此初始方法，这项工作的目标从单学科优化扩展到了多学科优化，其中包括EPS的设计和操作，姿态确定和控制系统（ADCS）以及通信系统。地面开发阶段的条件；但是，由于干扰，运行优化可能无法达到预期的轨道效果。为了解决这个问题，对于ADCS操作，开发并实现了基于模型预测控制的有效约束处理控制器。所有建议的设计和操作方法论都应用于“ CADRE”任务，该任务是计划于2016年运行的太空气象任务。该应用程序演示了该方法增强CADRE功能的有用性和能力，以及其适用于卫星的能力。各种任务。

著录项

  • 作者

    Lee, Dae Young.;

  • 作者单位

    University of Michigan.;

  • 授予单位 University of Michigan.;
  • 学科 Aerospace engineering.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 151 p.
  • 总页数 151
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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