This paper presents a novel hybrid method to design the continuous and accurate multi-gravity-assist trajectory for a high-fidelity dynamics.The gravitational perturbation of the primary body is considered during the ...This paper presents a novel hybrid method to design the continuous and accurate multi-gravity-assist trajectory for a high-fidelity dynamics.The gravitational perturbation of the primary body is considered during the gravity assistance.The pseudostate technique is applied to approximate the gravity-assisted trajectory,where the optimal sweepback duration is solved using a trained deep neural network.The major factors that affect the optimal sweepback duration of the approach and departure segments are investigated.The results show that the optimal sweepback duration of the approach segment only relies on the shape of the approach trajectory and is independent of the flight time.Then,a gravity-assisted trajectory patched strategy and a hybrid algorithm combining the particle swarm optimization and the sequential quadratic programming are developed to optimize the multi-gravity-assist trajectory.The proposed hybrid method is applied to the Europa orbiter mission.In comparison with the traditional patched conic method,this method demonstrates outstanding performance on accuracy and significantly reduces the computational time and complexity of the trajectory correction with the high-fidelity dynamics.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.61273051)the Qing Lan Project,Funding for Outstanding Doctoral Dissertation in NUAA(Grant No.BCXJ19-12)the State Scholarship from China Scholarship Council(Grant No.201906830066)。
文摘This paper presents a novel hybrid method to design the continuous and accurate multi-gravity-assist trajectory for a high-fidelity dynamics.The gravitational perturbation of the primary body is considered during the gravity assistance.The pseudostate technique is applied to approximate the gravity-assisted trajectory,where the optimal sweepback duration is solved using a trained deep neural network.The major factors that affect the optimal sweepback duration of the approach and departure segments are investigated.The results show that the optimal sweepback duration of the approach segment only relies on the shape of the approach trajectory and is independent of the flight time.Then,a gravity-assisted trajectory patched strategy and a hybrid algorithm combining the particle swarm optimization and the sequential quadratic programming are developed to optimize the multi-gravity-assist trajectory.The proposed hybrid method is applied to the Europa orbiter mission.In comparison with the traditional patched conic method,this method demonstrates outstanding performance on accuracy and significantly reduces the computational time and complexity of the trajectory correction with the high-fidelity dynamics.
