航空学报 > 2023, Vol. 44 Issue (S2): 729430-729430   doi: 10.7527/S1000-6893.2023.29430

亚轨道飞行器再入轨迹高精度自适应凸规划

刘哲1, 张羲格2, 韦常柱1(), 崔乃刚1   

  1. 1.哈尔滨工业大学 航天学院,哈尔滨  150001
    2.北京宇航系统工程研究所,北京  100076
  • 收稿日期:2023-08-10 修回日期:2023-08-11 接受日期:2023-09-13 出版日期:2023-10-07 发布日期:2023-09-27
  • 通讯作者: 韦常柱 E-mail:weichangzhu@hit.edu.cn
  • 基金资助:
    国家自然科学基金(52232014);1912项目

High-precision adaptive convex programming for reentry trajectories of suborbital vehicles

Zhe LIU1, Xige ZHANG2, Changzhu WEI1(), Naigang CUI1   

  1. 1.School of Aerospace,Harbin Institute of Technology,Harbin  150001,China
    2.Beijing Institute of Space System Engineering,Beijing  100076,China
  • Received:2023-08-10 Revised:2023-08-11 Accepted:2023-09-13 Online:2023-10-07 Published:2023-09-27
  • Contact: Changzhu WEI E-mail:weichangzhu@hit.edu.cn
  • Supported by:
    National Natural Science Foundation of China(52232014);1912 Project

摘要:

针对全要素终端状态约束下的亚轨道可重复使用飞行器再入滑翔轨迹规划精度不足、难收敛问题,提出了一种结合序列凸优化与自适应网格更新约束同伦模型预测凸规划的高精度求解算法,实现弱初值依赖条件下再入轨迹规划过程的高精度可靠收敛。首先,对部分终端约束进行松弛处理,并在凸优化求解过程中将信赖域作为软约束,定义反映线性化误差及约束违反程度的增广指标函数,采取多维参数搜索方式分别更新状态量及控制量,避免传统一维线搜索出现无解情况;进一步选取约束松弛项作为同伦参数,基于模型预测误差评估自适应调整离散网格,并构建考虑多约束的静态凸规划问题模型,同伦优化求取全程控制调整量,以实现全要素轨迹状态量高精度校正,提升算法收敛性。最终,通过数值仿真验证了本文方法的有效性。

关键词: 再入轨迹规划, 全要素约束, 凸优化, 模型预测校正, 自适应网格更新

Abstract:

Under complete terminal state constraints, the reentry gliding trajectory planning of suborbital reusable aircraft is short of convergence and accuracy. A high-precision solution algorithm combining sequential convex optimization and adaptive mesh refinement based homotopic constrained model predictive convex programming is proposed to achieve high-precision and reliable convergence in the reentry trajectory planning process under the conditions of weak initial value dependency. Firstly, several terminal constraints are relaxed, and the trust region is utilized as a soft constraint during the convex optimization process. An augmented index function is defined to reflect the linearization error and the degree of constraint violation. A multi-dimensional parameter search method is proposed to update the state and control variables separately, avoiding the situation of no solution in the basic line search. Further, constraint relaxation terms are selected as homotopy parameters, the discrete mesh is adjusted adaptively based on evaluation of model prediction deviation, and a static convex programming problem model is constructed considering multi-constraints. Then, the control adjustment quantity in the entire process is homotopically optimized to achieve high-precision correction of all-element trajectory state variables and improve algorithm convergence. Finally, the effectiveness of the proposed method is verified through numerical simulation.

Key words: reentry trajectory planning, complete constraints, convex optimization, model prediction correction, adaptive mesh refinement

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