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Robust Trajectory Optimization Techniques Using a Sweeping Gradient Method and Linear Covariance AnalysisWe present robust trajectory optimization techniques using a sweeping gradient method for ordinary differential equations with events (SGM) and linear covariance analysis (LinCov). SGM is a method for computing the gradient of trajectory analyses defined by performance indices over initial value problems with events with respect to static parameters. LinCov is an analytic technique for predicting stochastic behavior of dynamical systems. By combining SGM and LinCov, it is possible use efficient, off-the-shelf, gradient-based optimizers to solve robust optimal trajectory design problems. We describe the individual methods and some details on how they can be combined. Then we apply the combined techniques to a variety of orbital trajectory design problems to demonstrate its use, including minimum fuel transfer and mid-course correction burn scheduling.
Document ID
20240009432
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Benjamin W L Margolis
(Ames Research Center Mountain View, United States)
David Woffinden
(Johnson Space Center Houston, United States)
Date Acquired
July 23, 2024
Subject Category
Aeronautics (General)
Meeting Information
Meeting: AAS/AIAA Astrodynamics Specialist Conference
Location: Broomfield, Colorado
Country: US
Start Date: August 11, 2024
End Date: August 15, 2024
Sponsors: American Institute of Aeronautics and Astronautics
Funding Number(s)
WBS: 909018.36.40.02.21.02
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Technical Review
NASA Peer Committee
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