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Learning-based Control of a Spacecraft with Sloshing Propellant

机译:基于学习的航天器控制与晃动推进剂

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摘要

One of the major needs of present and future spacecraft is to fulfil highly demanding pointing requirements when performing attitude manoeuvres without losing stringent control over their flexible parts. For long-duration missions, the propellant mass is a significant portion of the overall mass budget of the satellite. The interaction between the fluid and the tank walls can lead to instability problems and even to mission failure if not properly accounted for in the design phase and control synthesis. The combined liquid–structure dynamic coupling is usually extremely difficult to model for a space system. An equivalent mechanical system is then desirable to carry out a computationally efficient simulation of the liquid behaviour inside the tank. In this paper, the 3D model of a spacecraft equipped with flexible appendages and tanks containing liquid propellant is presented. A learning-based control strategy using on-orbit available data is designed to improve the attitude tracking precision for repetitive on-orbit manoeuvres, compensating for cyclic disturbances such as liquid fuel sloshing effects. A co-simulation procedure between MSC Adams and Simulink is then carried out to test the performance of the controller. The effectiveness of the proposed control strategy is analysed and discussed, and conclusions are presented.
机译:当前和未来的航天器的主要需求之一是在表现态度操纵时满足高苛刻的指向要求,而不会对其灵活的部件进行严格控制。对于长期任务,推进剂质量是卫星整体大规模预算的重要部分。如果在设计阶段和控制合成中,流体和罐壁之间的相互作用可能导致不稳定问题,甚至在任务故障中均未适当地占算法。组合的液体结构动态耦合通常非常难以模拟空间系统。然后希望在罐内的液体行为进行计算上有效地进行计算上有效的模拟。本文介绍了配备有柔性阑尾和含有液体推进剂罐的航天器的3D模型。采用轨道可用数据的基于学习的控制策略旨在提高重复轨道运动的姿态跟踪精度,补偿循环干扰,例如液体燃料晃动效果。然后执行MSC ADAMS和Simulink之间的共模过程以测试控制器的性能。分析并讨论了拟议的控制策略的有效性,并介绍了结论。

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