Convex optimization of asteroid landing trajectories driven by solar radiation pressure  

作　　者：Chuanjun DONG Hongwei YANG Shuang LI Bo LI 

机构地区：[1]College of Astronautics,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China [2]Tianjin Key Laboratory of Microgravity and Hypogravity Environment Simulation Technology,Tianjin 300458,China [3]Tianjin Institute of Aerospace Mechanical and Electrical Equipment,Tianjin 300458,China

出　　处：《Chinese Journal of Aeronautics》2022年第12期200-211,共12页中国航空学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(No.12102177);the Natural Science Foundation of Jiangsu Province,China(No.BK20180410);the Young Elite Scientists Sponsorship Program by CAST,China(No.2018QNRC001);the Open Project Program of Tianjin Key Laboratory of Microgravity and Hypogravity Environment Simulation Technology,China(No.WDZL2020-07);the Foundation of Graduate Innovation Center at NUAA,China(No.kfjj20201503).

摘　　要：High-area/mass ratio landers driven by Solar Radiation Pressure(SRP)have potential applications for future asteroid landing missions.This paper develops a new convex optimization-based method for planning trajectories driven by SRP.A Minimum Landing Error(MLE)control problem is formulated to enable planning SRP-controlled trajectories with different flight times.It is transformed into Second Order Cone Programming(SOCP)successfully by a series of different convexification technologies.A trust region constraint and a modified MLE objective function are used to guarantee the convergence performance of the optimization algorithm.Thereafter,the SRP-driven trajectory optimal control problem is converted equivalently into a sequence of convex optimal control problems that can be solved effectively.A set of numerical simulation results has verified the effectiveness and feasibility of the proposed optimization method.

关 键 词：ASTEROIDS Convex optimization Optimal control Soft landing Solar radiation pressure Trajectory optimization 

分 类 号：V476.4[航空宇航科学与技术—飞行器设计] V448.2