基于混合粒子群算法的上升段交会弹道快速优化设计

基于梯度搜索的高效性和粒子群搜索的随机性,提出了一种混合粒子群算法,并应用该算法研究了运载火箭上升段交会弹道快速优化设计问题.以运载火箭与目标飞行器在交会时刻的距离最小为目标函数,设计了运载火箭飞行程序,建立了运载火箭上升段交会弹道优化模型,同时分别采用混合粒子群算法、遗传算法和粒子群算法进行求解.仿真结果表明:基于本文算法对运载火箭上升段交会弹道进行优化设计,平均交会位置误差为4.137m,较遗传算法减少了17.940m,平均优化耗时488.922s,较粒子群算法缩短了2342.125s.混合粒子群算法搜索速度较快,收敛精度较高,可用于运载火箭上升段交会弹道的快速优化设计. 

Rapid optimization design of ascent rendezvous trajectory for launch vehicles based on hybrid particle swarm algorithm

Based on efficiency of gradient search and randomness of particle swarm search, a hybrid particle swarm algorithm was proposed, and applied to research the rapid optimization design of ascent rendezvous trajectory for launch vehicles. Regarding the minimum distance between launch vehicles and target aircraft at intersection point as the objective function, the flight program of solid launch vehicles was designed and an optimization model of ascent rendezvous trajectory was established, and solved by the hybrid particle swarm algorithm, genetic algorithm and particle swarm algorithm. The simulation results indicat that:the algorithm can solve the optimization design problem effectively, the average error of rendezvous position is 4.137m, 17.940m less than genetic algorithm, and the average optimization time is 488.922s, 2342.125s shorter than particle swarm algorithm. The algorithm can be applied to the rapid optimization design of ascent rendezvous trajectory for launch vehicles because of its faster search speed and higher convergence accuracy.