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 six degree-of-freedom trajectory simulation of a PDV (Powered Descent Vehicle) 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-second-long maneuver with an amplitude of 5 percent 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.
Adaptive Control Allocation for Powered Descent Vehicles
AIAA Guidance, Navigation, and Control Conference (GNC 2018)
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2018
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Kissimmee, FL, United States
AIAA SciTech Forum & Exposition (SciTech 2018)
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2018
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Kissimmee, FL, United States
2018-01-08
Conference paper
No indication
English
Adaptive Control Allocation for Powered Descent Vehicles
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|Adaptive Control Allocation for Powered Descent Vehicles (AIAA 2018-1457)
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|Simultaneous Trajectory Optimization for Adaptive Powered Descent
Springer Verlag | 2023
|NTRS | 1985
|NTIS | 1985
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