Perturbed low-thrust geostationary orbit transfer guidance via polynomial costate estimation  

作　　者：Zhao LI Hengnian LI Fanghua JIANG Junfeng LI 

机构地区：[1]State Key Laboratory of Astronautic Dynamics,Xi’an Satellite Control Center,Xi’an 710043,China [2]School of Aerospace Engineering,Tsinghua University,Beijing 100084,China

出　　处：《Chinese Journal of Aeronautics》2024年第3期181-193,共13页中国航空学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(No.12022214);the National Key R&D Program of China(No.2020YFC2201200)。

摘　　要：This paper proposes an optimal,robust,and efficient guidance scheme for the perturbed minimum-time low-thrust transfer toward the geostationary orbit.The Earth’s oblateness perturbation and shadow are taken into account.It is difficult for a Lyapunov-based or trajectory-tracking guidance method to possess multiple characteristics at the same time,including high guidance optimality,robustness,and onboard computational efficiency.In this work,a concise relationship between the minimum-time transfer problem with orbital averaging and its optimal solution is identified,which reveals that the five averaged initial costates that dominate the optimal thrust direction can be approximately determined by only four initial modified equinoctial orbit elements after a coordinate transformation.Based on this relationship,the optimal averaged trajectories constituting the training dataset are randomly generated around a nominal averaged trajectory.Five polynomial regression models are trained on the training dataset and are regarded as the costate estimators.In the transfer,the spacecraft can obtain the real-time approximate optimal thrust direction by combining the costate estimations provided by the estimators with the current state at any time.Moreover,all these computations onboard are analytical.The simulation results show that the proposed guidance scheme possesses extremely high guidance optimality,robustness,and onboard computational efficiency.

关 键 词：Low thrust Orbital transfer Trajectory optimization GUIDANCE Indirect method Orbital averaging Machine learning Geostationary satellites 

分 类 号：V448[航空宇航科学与技术—飞行器设计]