Abstract
This paper presents a belief-based formulation and a novel approach for the robust solution of optimal control problems under uncertainty. The introduced formulation, based on the Belief Markov Decision Process model, reformulates the control problem directly in terms of uncertainty distributions, called beliefs, rather than on realisations of the system state. Successively, an approach inspired by navigation analysis is developed to transcribe and solve such problem in the presence of observation windows, employing a polynomial expansion for the dynamical propagation. Finally, the developed method is applied to the robust optimisation of a flyby trajectory of Europa Clipper mission in a scenario characterised by knowledge, execution and observation errors.
Original language | English |
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Pages | 1-25 |
Number of pages | 25 |
DOIs | |
Publication status | Published - 5 Jan 2020 |
Event | American Institute of Aeronautics and Astronautics (AIAA) SciTech Forum - Hyatt Regency Orlando , Orlando, United States Duration: 6 Jan 2020 → 10 Jan 2020 https://www.aiaa.org/SciTech |
Conference
Conference | American Institute of Aeronautics and Astronautics (AIAA) SciTech Forum |
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Abbreviated title | SciTech 2020 |
Country | United States |
City | Orlando |
Period | 6/01/20 → 10/01/20 |
Internet address |
Keywords
- optimal control
- Markov decision processes