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On-Board Model Based Fault Diagnosis for CubeSat Attitude Control Subsystem: Flight Data ResultsSelf-sufficient, robotic spacecraft require estimates of their hardware health state in order to project future system state and plan actions toward achieving mission goals. In this paper, we report on integration of a Model-Based Fault Diagnosis (MBFD) model and reasoning engine into flight software leveraging the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, including test results against captured flight data using the ASTERIA system testbed. Our effort integrated the Model-based Off-Nominal State Identification and Detection (MONSID) model-based reasoning system, developed by Okean Solutions, into ASTERIA flight software using the F Prime software framework. The MONSID engine was supplied with a model of the Blue Canyon Technologies XACT attitude control system (ACS) and tested against flight data and seeded fault tests. While we were unable to conduct an on-board experiment due to the premature loss of ASTERIA, our effort proved the feasibility of on-board model-based fault management, demonstrating reliable and accurate diagnosis using captured data, and further supporting a closed-loop spacecraft autonomy demonstration including autonomous navigation in off-nominal conditions.
Document ID
20220003776
Acquisition Source
Jet Propulsion Laboratory
Document Type
Preprint (Draft being sent to journal)
External Source(s)
Authors
Prather, Maurice
Litke, Matthew J.
Kolcio, Ksenia O.
Fesq, Lorraine
Sievers, Michael
Bocchino, Robert
Altenbuchner, Cornelia
Nikora, Allen
Mackey, Ryan M
Date Acquired
March 6, 2021
Publication Date
March 6, 2021
Publication Information
Publisher: Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2021
Distribution Limits
Public
Copyright
Other
Technical Review

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