TY - JOUR
T1 - Scheduling Optimization of Multiple Hybrid-Propulsive Spacecraft for Geostationary Space Debris Removal Missions
AU - Wei, Zhao
AU - Long, Teng
AU - Shi, Renhe
AU - Wu, Yufei
AU - Ye, Nianhui
N1 - Publisher Copyright:
© 1965-2011 IEEE.
PY - 2022/6/1
Y1 - 2022/6/1
N2 - To efficiently implement space debris removal missions on geostationary Earth orbit (GEO), a scheduling optimization scheme of multiple hybrid-propulsive servicing spacecraft (SSc) is proposed. In this scheme, a many-to-many task allocation coding model is established to formulate the removal sequences of debris targets with respect to different SSc. And a hybrid-propulsive orbit transfer strategy is developed to implement the debris removal maneuvers to save the propellant consumption and removal time simultaneously via using both electric and chemical propulsion systems. Then, the multiple GEO space debris removal scheduling optimization problem is formulated to minimize the total propellant consumption by exploring the optimal removal sequences and orbit maneuver parameters, subject to the available velocity increment, removal time, and many-to-many task allocation constraints. To effectively solve the scheduling optimization problem involving discrete-continuous mixed variables, a clustering based adaptive differential evolution algorithm with potential individual reservation (CADE-PIR) is proposed. In CADE-PIR, the k-means clustering method and potential individual reservation mutation strategy are employed to promote the convergence rate and performance of exploration and exploitation. In the end, a real-world GEO space debris removal mission with multiple SSc is investigated to demonstrate the effectiveness and practicality of the proposed optimization scheme.
AB - To efficiently implement space debris removal missions on geostationary Earth orbit (GEO), a scheduling optimization scheme of multiple hybrid-propulsive servicing spacecraft (SSc) is proposed. In this scheme, a many-to-many task allocation coding model is established to formulate the removal sequences of debris targets with respect to different SSc. And a hybrid-propulsive orbit transfer strategy is developed to implement the debris removal maneuvers to save the propellant consumption and removal time simultaneously via using both electric and chemical propulsion systems. Then, the multiple GEO space debris removal scheduling optimization problem is formulated to minimize the total propellant consumption by exploring the optimal removal sequences and orbit maneuver parameters, subject to the available velocity increment, removal time, and many-to-many task allocation constraints. To effectively solve the scheduling optimization problem involving discrete-continuous mixed variables, a clustering based adaptive differential evolution algorithm with potential individual reservation (CADE-PIR) is proposed. In CADE-PIR, the k-means clustering method and potential individual reservation mutation strategy are employed to promote the convergence rate and performance of exploration and exploitation. In the end, a real-world GEO space debris removal mission with multiple SSc is investigated to demonstrate the effectiveness and practicality of the proposed optimization scheme.
KW - Geostationary missions
KW - multiple hybrid-propulsive spacecraft
KW - scheduling optimization
KW - space debris removal
UR - http://www.scopus.com/inward/record.url?scp=85132338793&partnerID=8YFLogxK
U2 - 10.1109/TAES.2021.3131294
DO - 10.1109/TAES.2021.3131294
M3 - Article
AN - SCOPUS:85132338793
SN - 0018-9251
VL - 58
SP - 2304
EP - 2326
JO - IEEE Transactions on Aerospace and Electronic Systems
JF - IEEE Transactions on Aerospace and Electronic Systems
IS - 3
ER -