An integrated nonlinear planning(NLP) model is built for space station long-duration orbital missions considering both the vehicle visiting schedules and the interaction effects between target phasing,vehicle return a...An integrated nonlinear planning(NLP) model is built for space station long-duration orbital missions considering both the vehicle visiting schedules and the interaction effects between target phasing,vehicle return adjusting and Earth observation aiming.A two-level optimization approach is proposed to solve this complicated problem.The up-level problem employs the launch times of visiting vehicles as design variables,considers the constraints of crew rotations,resource resupplies and rendezvous launch windows,and is solved by a genetic algorithm.The low-level problems employ the maneuver impulses and burn times within each orbital mission as design variables,and a high-efficient shooting iteration method is proposed based on an analytical equation for the phase angle correction considering the J 2 perturbation.The results indicate that the integrated NLP model for space station long-duration orbital missions is effective,and the proposed optimization approach can obtain the optimal solutions that satisfy the multiple constraints and reduce the total propellant consumption.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.11222215)the Foundation for the Author of National Excellent Doctoral Dissertation of China(Grant No.201171)
文摘An integrated nonlinear planning(NLP) model is built for space station long-duration orbital missions considering both the vehicle visiting schedules and the interaction effects between target phasing,vehicle return adjusting and Earth observation aiming.A two-level optimization approach is proposed to solve this complicated problem.The up-level problem employs the launch times of visiting vehicles as design variables,considers the constraints of crew rotations,resource resupplies and rendezvous launch windows,and is solved by a genetic algorithm.The low-level problems employ the maneuver impulses and burn times within each orbital mission as design variables,and a high-efficient shooting iteration method is proposed based on an analytical equation for the phase angle correction considering the J 2 perturbation.The results indicate that the integrated NLP model for space station long-duration orbital missions is effective,and the proposed optimization approach can obtain the optimal solutions that satisfy the multiple constraints and reduce the total propellant consumption.
