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对于长期太空任务中循环生命支持系统的监管模型预测控制
Gionata Cimini1, Marco Gatti2, Daniele Bernardini1
1ODYS S.r.l., Milan, Italy.
Life sciences in space research
|October 24, 2025
概括
再生生命支持系统 (LSS) 对于太空任务至关重要. 一种新的模型预测控制 (MPC) 方法提高了这些复杂系统的控制和可靠性,使用MELiSSA项目证明了这一点.
科学领域:
- 太空探索技术的技术
- 控制系统工程 控制系统工程
- 环境工程环境工程
背景情况:
- 再生生命支持系统 (LSS) 对于长期太空任务至关重要,提供必要的生存功能.
- LSS的复杂性,效率和可靠性给运营带来了重大挑战.
- 协调不同的子系统 (机械,化学,生物,能源) 是满足任务要求的关键.
研究的目的:
- 为再生LSS提出一个监管控制层.
- 为了应对LSS运行的复杂性,效率和可靠性的挑战.
- 通过使用全面的动态模型验证拟议的控制策略.
主要方法:
- 开发一个非线性和时间变化的模型预测控制 (MPC) 监管层.
- 为欧洲航天局的MELiSSA (微生态生命支持系统替代方案) 项目创建一个完整的动态模型,整合所有部分和阶段 (固体,液体,气体).
- 使用MPC方法模拟和控制MELiSSA系统.
主要成果:
- 通过监管MPC首次导出,模拟和控制一个完整的MELiSSA动态模型.
- 在14周的任务中,控制的MELiSSA系统成功运行.
- 通过模拟故障场景来证明系统的弹性.
结论:
- 拟议的MPC监管控制层有效地管理复杂的再生LSS.
- 该方法提高了太空探索生命支持系统的可靠性和效率.
- 这项工作为控制未来先进的LSS提供了一个强大的框架.
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