基于子集模拟优化的空天飞机再入轨迹混合优化方法

A Hybrid Optimization Method for Reentry Trajectory of Space Plane Based on Subset Simulation Optimization

提出采用一种新的随机优化算法(子集模拟优化算法)来改进现有的空天飞机再入轨迹混合优化方法。这种混合优化方法的思路是:首先在整个设计空间使用子集模拟优化算法进行全局搜索,迭代适当步数。之后,将其计算结果作为初值,用序列二次规划法优化算法进行再次优化,收敛后得到最终优化结果。算例证明,对于不同的精度要求,这种混合优化方法能均有效地求解空天飞机再入轨迹优化问题,且计算量较少。

A new stochastic optimization algorithm named as subset simulation optimization （SSO） is adopted to improve efficiency and robustness of the hybrid optimization method for space plane reentry trajectory in this paper. Firstly, the subset simulation optimization algorithm is utilized for global searching with appropriate iteration steps in the entire design space. Secondly, the optimal result generated by applying the SSO/s used us the initial values. Finially, the sequential quadratic programming optimization algorithm is used to find the final optimization results after convergence. Moreover, a case study is used to validate the proposed method. The results indicate that the reentry trajectory optimization problem can be robustly solved with less computational burden for the various precision requirements.