Trajectory planning for satellite cluster reconfigurations with sequential convex programming method

This paper presents trajectory planning algorithms for large-scale satellite clusters reconfiguration based on sequential convex programming, and these algorithms consider fuel consumption and collision avoidance. Firstly, the trajectory planning problem is formulated as a nonconvex optimal control...

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Veröffentlicht in:Aerospace science and technology Jg. 136; S. 108216
Hauptverfasser: Wang, Lixiang, Ye, Dong, Xiao, Yan, Kong, Xianren
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Masson SAS 01.05.2023
Schlagworte:
Collision avoidance
Large-scale satellite cluster
Sequential convex programming
Trajectory planning
Sequential convex programming
Large-scale satellite cluster
Trajectory planning
Collision avoidance
ISSN:1270-9638
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Zusammenfassung:This paper presents trajectory planning algorithms for large-scale satellite clusters reconfiguration based on sequential convex programming, and these algorithms consider fuel consumption and collision avoidance. Firstly, the trajectory planning problem is formulated as a nonconvex optimal control problem with nonlinear dynamics and nonconvex path constraints. Secondly, the original nonlinear continuous optimal control problem is transformed into a discrete convex optimization subproblem through linearization and discretization. Collision avoidance strategy between discrete points and obstacle avoidance constraints are considered in the convex subproblem to ensure that the trajectories are collision-free. Thirdly, coupled and decoupled sequential convex programming methods are proposed for rapidly generating collision-free and fuel-efficient trajectories. Finally, comparative numerical simulations are presented to demonstrate that as the number of satellites increases, 94 to 99 percent performance improvement over the pseudo-spectral method is achieved in terms of computational efficiency.
ISSN:1270-9638
DOI:10.1016/j.ast.2023.108216