基于混沌粒子群算法的跳跃-滑翔轨迹优化

Skip-Glide Trajectory Optimization Based on Chaotic Particle Swarm Optimization Algorithm

研究了一种高超声速跳跃-滑翔弹道方案。通过末级发动机多次点火,将再入弹道设计成临近空间的跳跃-滑翔弹道,在满足过程约束和航程约束的前提下实现总加热量最小的目标。采用混沌粒子群算法优化轨迹,通过引入混沌扰动避免算法早熟收敛。最后通过对高升阻比再入滑翔飞行器CAV-H的仿真分析,验证了优化算法的有效性。

A hypersonic skip-glide trajectory is introduced in this paper. By the multiple ignitions of final- stage motors, a skip-glide trajectory across the near-space is designed. Chaotic particle swarm optimization is proposed to achieve the goal of minimizing the total heat quantity under the condition of satisfying the process constraints and range constraint. Premature convergence is avoided by introducing the chaos disturb- ance. And a numerical simulation is performed, which is based on the high-lifting common aerial vehicle （CAV-H） model and the effectiveness of the method is demonstrated by the simulation results