Optimal plan for multiple debris removal missions
RAIRO - Operations Research - Recherche Opérationnelle, Tome 51 (2017) no. 4, pp. 1005-1032.

In order to keep a safe access to space in the coming years, it will be necessary to clean the near Earth region from the most dangerous debris like spent satellites or launchers stages. An average removal rate of 5 debris per year is recommended to at least stabilize the current debris population. Successive missions must be planned over the years using similar vehicles in order to limit the development cost. This paper addresses the problem of the mission plan so that they can be achieved at minimal cost by a generic vehicle designed for such Space Debris Collecting missions. The problem mixes combinatorial optimization to select and order the debris among a list of candidates, and continuous optimization to fix the rendezvous dates and to define the minimum fuel orbital maneuvers. The solution method proposed consists in three stages. Firstly the orbital transfer problem is simplified by considering a generic transfer strategy suited either to a high thrust or a low thrust vehicle. A response surface model is built by solving the reduced problem for all pairs of debris and for discretized dates, and storing the results in cost matrices. Secondly a simulated annealing algorithm is applied to find the optimal mission plan. The cost function is assessed by interpolation on the response surface based on the cost matrices. This allows the convergence of the simulated algorithm in a limited computation time, yielding an optimal mission plan. Thirdly the successive missions are re-optimized in terms of transfer maneuvers and dates without changing the debris order. These continuous control problems yield a refined solution with the performance requirement for designing the future Space Debris Collecting vehicle. The method is applicable for a large list of debris and for various assumptions regarding the cleaning program (number of missions, number of debris per mission, total duration, deorbitation scenario, high or low thrust vehicle). It is exemplified on an application case with 3 missions to plan, each mission visiting 5 sun-synchronous debris to be selected in a list of 21 candidates.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2017009
Classification : 90C27, 90C90, 93C95
Mots-clés : Space debris, orbital transfer, low thrust, simulated annealing
Cerf, Max 1

1 AIRBUS Defence and Space, 78130 Les Mureaux, France.
@article{RO_2017__51_4_1005_0,
     author = {Cerf, Max},
     title = {Optimal plan for multiple debris removal missions},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {1005--1032},
     publisher = {EDP-Sciences},
     volume = {51},
     number = {4},
     year = {2017},
     doi = {10.1051/ro/2017009},
     mrnumber = {3783932},
     zbl = {1393.90101},
     language = {en},
     url = {http://archive.numdam.org/articles/10.1051/ro/2017009/}
}
TY  - JOUR
AU  - Cerf, Max
TI  - Optimal plan for multiple debris removal missions
JO  - RAIRO - Operations Research - Recherche Opérationnelle
PY  - 2017
SP  - 1005
EP  - 1032
VL  - 51
IS  - 4
PB  - EDP-Sciences
UR  - http://archive.numdam.org/articles/10.1051/ro/2017009/
DO  - 10.1051/ro/2017009
LA  - en
ID  - RO_2017__51_4_1005_0
ER  - 
%0 Journal Article
%A Cerf, Max
%T Optimal plan for multiple debris removal missions
%J RAIRO - Operations Research - Recherche Opérationnelle
%D 2017
%P 1005-1032
%V 51
%N 4
%I EDP-Sciences
%U http://archive.numdam.org/articles/10.1051/ro/2017009/
%R 10.1051/ro/2017009
%G en
%F RO_2017__51_4_1005_0
Cerf, Max. Optimal plan for multiple debris removal missions. RAIRO - Operations Research - Recherche Opérationnelle, Tome 51 (2017) no. 4, pp. 1005-1032. doi : 10.1051/ro/2017009. http://archive.numdam.org/articles/10.1051/ro/2017009/

Position paper on space debris mitigation. International Academy of Astronautics (2005).

H. Klinkrad, Space Debris. Models and Risks Analysis. Springer (2006).

J. Liou, An assessment of the current LEO debris environment and what needs to be done to preserve it for future generations (2008).

R. Walker, C.E. Martin, P.H. Stokes and J.E. Wilkinson, Studies of space debris mitigation options using the debris environment long term analysis (DELTA) model. In: 51st International Astronautical Congress, Brazil, Rio de Janeiro (2000).

G.L. Nemhauser, A.H.G. Rinnooy and Kan M.J. Todd, Optimization, Handbooks in operations research and management science, Volume 1. Elsevier (1989). | Zbl

J. Dréo, A. Pétrowski, P. Siarry and E. Taillard. Métaheuristiques pour l’optimisation difficile. Eyrolles (2003).

J.J. Schneider and S. Kirkpatrick, Stochastic optimization. Springer (2006). | MR | Zbl

M. Cerf, Multiple space debris collecting mission, debris selection and trajectory optimization. J. Optim. Theory Appl. 156 (2013) 761–796. | DOI | MR | Zbl

V. Chobotov, Orbital mechanics - Third Edition. AIAA Education Series (2002). | Zbl

D.A. Vallado, Fundamentals of Astrodynamics and Applications - Third Edition. Space Technology Library (2007). | MR | Zbl

G. Leitmann, Theory of maxima and minima, Optimization technique with applications to Aerospace System, Academic, New York (1962). | MR

B.A. Conway, Spacecraft Trajectory Optimization. Cambridge University Press (2010).

TSPLIB (Traveling Salesman Problems test cases database) https://www.iwr.uni-heidelberg.de/groups/comopt/software/TSPLIB95/ (2013).

NORAD Two Line Elements. http://www.celestrak.com/NORAD/elements/.

Cité par Sources :