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Adaptive Control Allocation for Powered Descent Vehicles

机译:动力下降车辆的自适应控制分配

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The following work details a study into real-time failure adaptive control allocation method for powered descent vehicle systems. The motivation for this work is to enable future human and robotic missions utilizing a powered descent system to tolerate engine failures in flight without the loss of crew or assets. This study is conducted using a si. degree-of-freedom trajectory simulation of a PDV experiencing either a loss of thrust or an engine stuck full on failure scenario. Sequential least squares in the frequency domain is used on-board to process inertial measurement unit (IMU) data and generate an estimate of the PDV plant model, which is then fed to the guidance and control system. Data used by the sequential least squares method is generated from an in-flight maneuver. The work herein focuses on determining a maneuver that is least impactful to the PDV trajectory and enables a suitable plant model estimate. A 1.5 s long maneuver with an amplitude of 5% throttle is determined to provide suitable data for the sequential least squares method to estimate a plant model. A PDV implementing this method can adapt to a single engine failure and continue to reach its touchdown conditions.
机译:以下工作详情详细介绍了动力下降车辆系统实时故障自适应控制分配方法。这项工作的动机是为了使未来的人类和机器人任务利用动力的下降系统来容忍飞行中的发动机故障而不会损失机组人员或资产。本研究使用SI进行。\自由度轨迹模拟,其PDV体现出损失的推力或发动机在故障场景上陷入困境。频域中的序列最小二乘用途用于处理惯性测量单元(IMU)数据,并生成PDV工厂模型的估计,然后将其馈送到引导和控制系统。序列最小二乘法使用的数据是从飞行中的操纵生成的。这里的工作侧重于确定对PDV轨迹最不影响的机动,并且能够实现合适的植物模型估计。确定具有5%节流阀的1.5秒的长机动,以提供用于估计植物模型的序列最小二乘法的合适数据。 PDV实现此方法可以适应单个发动机故障并继续达到其触地趋势。

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