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Robust Fault Diagnosis for Atmospheric Reentry Vehicles: A Case Study

机译:大气再入飞行器的鲁棒故障诊断:一个案例研究

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This paper deals with the design of robust model-based fault detection and isolation (FDI) systems for atmospheric reentry vehicles. This work draws expertise from actions undertaken within a project at the European level, which develops a collaborative effort between the University of Bordeaux, the European Space Agency, and European Aeronautic Defence and Space Company Astrium on innovative and robust strategies for reusable launch vehicles (RLVs) autonomy. Using an ${cal H}_{infty}/{cal H}_{-}$ setting, a robust residual-based scheme is developed to diagnose faults on the vehicle wing-flap actuators. This design stage is followed by an original and specific diagnosis-oriented analysis phase based on the calculation of the generalized structured singular value. The latter provides a necessary and sufficient condition for robustness and FDI fault sensitivity over the whole vehicle flight trajectory. A key feature of the proposed approach is that the coupling between the in-plane and out-of-plane vehicle motions, as well as the effects that faults could have on the guidance, navigation, and control performances, are explicitly taken into account within the design procedure. The faulty situations are selected by a prior trimmability analysis to determine those for which the remaining healthy control effectors are able to maintain the vehicle around its center of gravity. Finally, some performance indicators including detection time, required onboard computational effort, and CPU time consumption are assessed and discussed. Simulation results are based on a nonlinear benchmark of the HL-20 vehicle under realistic operational conditions during the autolanding phase. The Monte Carlo results are quite encouraging, illustrating clearly the effectiveness of the proposed technique and suggesting that this solution could be considered as a viable candidate for future RLV programs.
机译:本文研究了大气再入飞行器基于健壮模型的故障检测和隔离(FDI)系统的设计。这项工作从欧洲一级项目中采取的行动中汲取了专业知识,该项目在波尔多大学,欧洲航天局和欧洲航空防卫与航天公司Astrium之间开展了有关可重复使用运载火箭(RLVs)的创新而强大的战略的合作。 )自治。使用$ {cal H} _ {infty} / {cal H} _ {-} $设置,开发了一种基于残差的鲁棒方案,以诊断车辆机翼襟翼执行器上的故障。此设计阶段之后是基于广义结构化奇异值的计算的原始且面向诊断的特定分析阶段。后者为整个飞行轨迹上的鲁棒性和FDI故障敏感性提供了必要和充分的条件。所提出的方法的一个关键特征是,在平面内和平面内车辆运动之间的耦合以及故障可能对制导,导航和控制性能产生的影响已被明确考虑在内。设计程序。通过事先的可修整性分析来选择故障状况,以确定剩余的健康控制执行器能够将车辆保持在其重心附近的状况。最后,评估和讨论了一些性能指标,包括检测时间,所需的机载计算量以及CPU时间消耗。仿真结果基于HL-20车辆在自动着陆阶段实际运行条件下的非线性基准。蒙特卡洛的结果令人鼓舞,清楚地说明了所提出技术的有效性,并暗示该解决方案可以被视为未来RLV计划的可行候选者。

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