一种高超声速飞行器再入轨迹优化方法

针对高超声速飞行器的再入轨迹优化问题，提出了一种基于动态自适应樽海鞘群算法和高斯伪谱法的混合优化方案。首先，为了使樽海鞘群算法探索和利用之间的平衡更加合理，提出了一种新颖的动态自适应樽海鞘群算法。然后，针对传统高斯伪谱法在轨迹优化过程中对初始猜测值敏感的不足，借助动态自适应樽海鞘群算法强大的全局搜索能力，先利用该算法对控制量进行全局寻优，将求得的近似全局最优解作为高斯伪谱法优化的初始猜测值，接着再利用高斯伪谱法对控制量进行全局寻优。仿真结果表明所提出的动态自适应樽海鞘群算法和混合优化方案的有效性和可行性。

A Reentry Trajectory Optimization Method for Hypersonic Vehicles

In this paper, a hybrid optimization scheme based on the dynamic adaptation salp swarm algorithm and Gauss pseudospectral method is proposed for the reentry trajectory optimization problem of hypersonic vehicles. Firstly, to make the exploration and exploitation process of the salp swarm algorithm more appropriate, a novel dynamic adaptation salp swarm algorithm is developed. Then, for the drawback that the Gauss pseudospectral method is sensitive to the initial guess, a dynamic adaptation salp swarm algorithm is employed to optimize the control variables first for its strong global search capability. The obtained approximate global optimal solution is taken as the initial guess, and the Gauss pseudospectral method is utilized to optimize the control variables sequentially. The simulations verify the effectiveness and feasibility of the proposed dynamic adaptation salp swarm algorithm and hybrid optimization scheme.