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Integrated Space Logistics Mission Planning and Spacecraft Design with Mixed-Integer Nonlinear Programming

机译:混合整数非线性规划的综合空间物流任务计划与航天器设计

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This paper develops a campaign-level space logistics optimization framework that considers mission planning and spacecraft design simultaneously utilizing mixed integer nonlinear programming (MINP). In the mission planning part of the framework, deployment and utilization of in-orbit infrastructures such as in-orbit propellant depot or in-situ resource utilization (ISRU) plant are also taken into account. Two methods are proposed: First, the MINP is converted into a mixed-integer linear programming (MILP) after approximating the nonlinear model by piecewise function and linearizing quadratic terms. In addition, another optimization framework is provided based on simulated annealing (SA) which separates spacecraft model from mission planning formulation. An example mission scenario based on multiple Apollo missions is considered and the results show a significant improvement in the initial mass in low-Earth orbit (IMLEO) by campaign-level design compared with the traditional mission-level design. It is also shown that the SA-based method is harder to achieve global optimum than the MILP-based method in a reasonable time, but it is more flexible for extension to a higher fidelity spacecraft model.
机译:本文开发了一个战役级空间物流优化框架,该框架同时考虑了利用混合整数非线性规划(MINP)进行的任务计划和航天器设计。在该框架的任务计划部分,还考虑了在轨基础设施的部署和利用,例如在轨推进剂仓库或在地资源利用(ISRU)工厂。提出了两种方法:首先,通过分段函数逼近非线性模型并将二次项线性化,然后将MINP转换为混合整数线性规划(MILP)。此外,基于模拟退火(SA)提供了另一个优化框架,该框架将航天器模型与任务计划制定分开了。考虑了基于多个阿波罗任务的示例任务场景,结果表明,与传统的任务级别设计相比,通过战役级别的设计,低地球轨道(IMLEO)的初始质量有了显着改善。还表明,在合理的时间内,基于SA的方法比基于MILP的方法更难实现全局最优,但是对于扩展到更高保真度的航天器模型则更加灵活。

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    《AIAA space forum》|2016年|2949-2981|共33页
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    Hao Chen; Koki Ho;

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