基于粒子群算法的固体运载火箭上升段弹道优化设计研究

A Particle Swarm Optimization Algorithm-Based Solid Launch Vehicle Ascent Trajectory Optimum Design

应用粒子群优化算法研究了固体运载火箭上升段弹道优化设计问题。设计了固体运载火箭上升段飞行程序,构建了固体运载火箭弹道优化设计问题的粒子群算法,通过控制参数改进和引入函数拉伸策略,对算法进行了改进。仿真计算结果表明,粒子群优化算法能有效解决固体运载火箭弹道优化设计问题,优化方案末助推级液体推进剂消耗比原方案减少11.1%,算法收敛速度快,需设置参数少,易于工程实现。可为固体运载火箭弹道优化设计提供理论参考。

The paper researches the optimum design of solid launch vehicle ascent trajectory using particle swarm optimization algorithm.The flight program of solid launch vehicle is designed,a particle swarm optimization algorithm for trajectory optimization is established,and the optimization algorithm was modified by improving the control parameters and adopting a function stretching strategy.Simulation results show that the particle swarm optimization algorithm can solve the problem of ascent trajectory optimization for multi-stage solid launch vehicle effectively,and propellant consumption of the upstage in optimization scheme is 11.1% less than primary scheme.The result also indicates that particle swarm optimization algorithm can reach convergence rapidly,the control parameters needed to be set is few,as a result,the algorithm can be easily realized in project.All those can provide theoretical reference for the research of solid launch vehicle optimum trajectory design.