TY - JOUR
T1 - Satellite Constellation Reconfiguration Using Surrogate-Based Optimization
AU - Zuo, Xiaoyu
AU - Bai, Xue
AU - Xu, Ming
AU - Li, Ming
AU - Zhou, Jing
AU - Yu, Linghui
AU - Zhang, Jingrui
N1 - Publisher Copyright:
© 2022 American Society of Civil Engineers.
PY - 2022/7/1
Y1 - 2022/7/1
N2 - The reconfiguration of a constellation with several faulty satellites concerns performance improvements in multiple fields, which can be regarded as a multiobjective optimization (MOO) problem. In the optimization design, it is inevitable to evaluate the constellation performance and providing the reconfiguration strategy thousands of times is time-consuming. To decrease the high computational expense, this paper proposes an accurate and efficient MOO method based on the kriging surrogate model, termed as the surrogate-based MOO (SBMOO) algorithm. A new hybrid refinement method is presented to select infilling samples for updating the surrogate model. Different from the orbital phasing maneuver, the low-thrust reconfiguration strategy is implemented to optimize the transfer trajectory with low fuel consumption, by changing the orbital inclination and right ascension of the ascending node. With the tradeoff between the constellation performance and the uniformity of fuel consumption, the MOO problem of constellation reconfiguration can be investigated and settled by the proposed SBMOO algorithm. The simulations confirm that the preferable constellation reconfigurations are achieved with a low computational expense for optimization and a low fuel cost for orbital transfer.
AB - The reconfiguration of a constellation with several faulty satellites concerns performance improvements in multiple fields, which can be regarded as a multiobjective optimization (MOO) problem. In the optimization design, it is inevitable to evaluate the constellation performance and providing the reconfiguration strategy thousands of times is time-consuming. To decrease the high computational expense, this paper proposes an accurate and efficient MOO method based on the kriging surrogate model, termed as the surrogate-based MOO (SBMOO) algorithm. A new hybrid refinement method is presented to select infilling samples for updating the surrogate model. Different from the orbital phasing maneuver, the low-thrust reconfiguration strategy is implemented to optimize the transfer trajectory with low fuel consumption, by changing the orbital inclination and right ascension of the ascending node. With the tradeoff between the constellation performance and the uniformity of fuel consumption, the MOO problem of constellation reconfiguration can be investigated and settled by the proposed SBMOO algorithm. The simulations confirm that the preferable constellation reconfigurations are achieved with a low computational expense for optimization and a low fuel cost for orbital transfer.
KW - Constellation reconfiguration
KW - Jordan normal form
KW - Multiobjective optimization (MOO)
KW - Surrogate model
UR - http://www.scopus.com/inward/record.url?scp=85128453251&partnerID=8YFLogxK
U2 - 10.1061/(ASCE)AS.1943-5525.0001438
DO - 10.1061/(ASCE)AS.1943-5525.0001438
M3 - Article
AN - SCOPUS:85128453251
SN - 0893-1321
VL - 35
JO - Journal of Aerospace Engineering
JF - Journal of Aerospace Engineering
IS - 4
ER -