宇航学报 ›› 2021, Vol. 42 ›› Issue (11): 1416-1426.doi: 10.3873/j.issn.1000-1328.2021.11.008

• 制导、导航、控制与电子 • 上一篇    下一篇

大气层内固体火箭实时轨迹优化方法

郝泽明,张冉,王嘉炜,李惠峰   

  1. 北京航空航天大学宇航学院,北京 100083
  • 收稿日期:2020-12-23 修回日期:2021-03-26 出版日期:2021-11-15 发布日期:2021-11-15

Real time Atmospheric Trajectory Optimization for Solid Rockets

HAO Ze ming, ZHANG Ran, WANG Jia wei, LI Hui feng   

  1. School of Astronautics, Beihang University, Beijing 100083, China
  • Received:2020-12-23 Revised:2021-03-26 Online:2021-11-15 Published:2021-11-15

摘要: 针对大气层内固体火箭能量管理问题,提出一种邻近-牛顿-康托维奇凸规划的实时轨迹优化方法。首先,针对传统能量管理方法难以严格满足大气层内过程约束的不足,提出了一种对控制量模值积分进行惩罚的规则化方法,将能量管理问题转化为轨迹优化问题。然后,针对大气层内强非线性动力学与约束,提出一种邻近-牛顿-康托维奇凸规划方法,对优化问题中的非线性项进行线性化处理并在性能指标中引入邻近规则化项,提升了算法的收敛性。最后,为减小优化算法对初始猜想的依赖性,引入虚拟控制变量对控制约束与过程约束进行松弛。数学仿真结果表明:采用所提出的轨迹优化方法求解能量管理问题是有效的,能够严格满足各项约束并实现高精度终端;此外,算法具有优异的实时性,能够满足能量管理对求解速度的要求。


关键词: 固体火箭能量管理, 大气层上升段, 轨迹优化, 凸规划

Abstract: This paper proposes a real time trajectory optimization method based on the Proximal Newton Kantorovich convex programming for the energy management of a solid rocket in atmosphere. In order to solve the problem that traditional energy management method is difficult to strictly satisfy the atmospheric process constraints, a regularization method is proposed first to punish the modular integral of control variables, transforming the energy management problem to the trajectory optimization problem. Then, for the strong nonlinear dynamics and constraints in the atmosphere, a Proximal Newton Kantorovich convex programming method is proposed, which linearizes the nonlinear term in the optimization problem and introduces the proximal term in the performance index to improve the convergence of the algorithm. Finally, the virtual control variables are introduced to relax the control constraints and process constraints to reduce the dependence of the optimization algorithm on the initial guess. The mathematical simulation shows that the proposed trajectory optimization method is effective to solve the energy management problem, which can strictly satisfy the constraints and achieve high accuracy terminal. In addition, the algorithm has good real time performance, which can meet the requirements of energy management for calculating speed.


Key words: Solid rocket energy management, Atmospheric ascent phase, Trajectory optimization, Convex programming

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