Advances in Trajectory Optimization for Space Vehicle Control
- URL: http://arxiv.org/abs/2108.02335v1
- Date: Thu, 5 Aug 2021 01:36:27 GMT
- Title: Advances in Trajectory Optimization for Space Vehicle Control
- Authors: Danylo Malyuta, Yue Yu, Purnanand Elango, Behcet Acikmese
- Abstract summary: This survey paper provides a detailed overview of recent advances, successes, and promising directions for optimization-based space vehicle control.
The considered applications include planetary landing, rendezvous and proximity operations, small body landing, constrained reorientation, endo-atmospheric flight.
The reader will come away with a well-rounded understanding of the state-of-the-art in each space vehicle control application.
- Score: 2.8557067479929152
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Space mission design places a premium on cost and operational efficiency. The
search for new science and life beyond Earth calls for spacecraft that can
deliver scientific payloads to geologically rich yet hazardous landing sites.
At the same time, the last four decades of optimization research have put a
suite of powerful optimization tools at the fingertips of the controls
engineer. As we enter the new decade, optimization theory, algorithms, and
software tooling have reached a critical mass to start seeing serious
application in space vehicle guidance and control systems. This survey paper
provides a detailed overview of recent advances, successes, and promising
directions for optimization-based space vehicle control. The considered
applications include planetary landing, rendezvous and proximity operations,
small body landing, constrained reorientation, endo-atmospheric flight
including ascent and re-entry, and orbit transfer and injection. The primary
focus is on the last ten years of progress, which have seen a veritable rise in
the number of applications using three core technologies: lossless
convexification, sequential convex programming, and model predictive control.
The reader will come away with a well-rounded understanding of the
state-of-the-art in each space vehicle control application, and will be well
positioned to tackle important current open problems using convex optimization
as a core technology.
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