Efficient optimization method for variable-specific-impulse low-thrust trajectories with shutdown constraint

作     者：JIA FeiDa QIAO Dong HAN HongWei LI XiangYu JIA FeiDa;QIAO Dong;HAN HongWei;LI XiangYu

作者机构：School of Aerospace EngineeringBeijing Institute of TechnologyBeijing 100081China Key Laboratory of Autonomous Navigation and Control for Deep Space ExplorationMinistry of Industry and Information TechnologyBeijing 100081China 

出 版 物：《Science China(Technological Sciences)》 (中国科学（技术科学英文版）)

年 卷 期：2022年第65卷第3期

页      面：581-594页

核心收录：

学科分类：080703[工学-动力机械及工程] 08[工学] 0807[工学-动力工程及工程热物理] 0805[工学-材料科学与工程（可授工学、理学学位）] 

基　　金：supported by the National Key R&D Program of China(Grant No.2020YFC2201200) the National Natural Science Foundation of China(Grant No.U20B2001)。 

主　　题：low-thrust trajectory variable-specific-impulse shutdown constraint sequential convex programming switching self-detection and adaptive node refinement 

摘      要：This paper develops a sequential convex programming(SCP)-based method to solve the minimum-fuel variable-specific-impulse low-thrust transfer problem considering shutdown constraint,with emphasize on improving the computational efficiency.The variable parameter engine is more applicable for many low-thrust scenarios,therefore,both a continuously variable model and a ladder variable model are adopted.First,the original problem is convexified by processing the constraint feasible domain,which is composed of the nonlinear dynamic equations and second-order equality constraint,into convex sets.Then,the approximation is generated to close the optimal solution of the low-thrust problem by iteratively solving the convexified subproblem.Moreover,the switching self-detection and adaptive node refinement methods are presented,which can improve the accuracy of the solution and accelerate the convergence during the approximation process and is especially necessary and effective in the scenarios with shutdown constraint.In numerical simulations,the comparison with the homotopic approach shows that the proposed method only needs 4%computational time as that of the homotopic approach,and two variable-specificimpulse examples further demonstrate the effectiveness and efficiency of the proposed method.