Optimal Abort Guidance and Experimental Verification Based on Feature Learning
Publication: Journal of Aerospace Engineering
Volume 37, Issue 2
Abstract
The abort mission refers to the mission where the landing vehicle needs to terminate the landing mission when an anomaly happens and be safely guided to the desired orbit. This paper focuses on solving the time-optimal abort guidance (TOAG) problem in real-time via the feature-based learning method. First, according to the optimal control theory, the features are identified to represent the optimal solutions of TOAG using a few parameters. After that, a sufficiently large data set of time-optimal abort trajectories is generated offline by solving the TOAG problems with different initial conditions. Then, the features are extracted for all generated cases. To find the implicit relationships between the initial conditions and identified features, neural networks are constructed to map the relationships based on the generated data set. Finally, experimental flight tests are conducted to demonstrate the onboard computation capability and effectiveness of the proposed method.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
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Information & Authors
Information
Published In
Journal of Aerospace Engineering
Volume 37 • Issue 2 • March 2024
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Dec 27, 2022
Accepted: Oct 17, 2023
Published online: Dec 30, 2023
Published in print: Mar 1, 2024
Discussion open until: May 30, 2024
ASCE Technical Topics:
- Aerospace engineering
- Aircraft and spacecraft
- Artificial intelligence and machine learning
- Astronomy
- Business management
- Computer programming
- Computing in civil engineering
- Engineering fundamentals
- Flight
- Geomatics
- Highway transportation
- Infrastructure
- Mapping
- Mathematics
- Methodology (by type)
- Neural networks
- Orbits
- Parameters (statistics)
- Practice and Profession
- Public administration
- Public health and safety
- Research methods (by type)
- Safety
- Statistics
- Surveying methods
- Transportation engineering
- Vehicles
- Verification
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