基于微粒群算法的中制导弹道优化设计

邵雷1,雷虎民1,张建新2,赵宗宝1

(1 空军工程大学 防空反导学院,西安 710051;2 中国人民解放军786厂军代室,西安 710043)

摘要:为使拦截武器有效拦截目标,将直接多重打靶算法与微粒群算法相结合,设计了一种基于微粒群算法的中制导弹道优化算法。该算法借鉴直接多重打靶算法基本思想,将状态空间与参数空间分别进行分解与分段,并在此基础上结合中制导末端条件构建性能指标函数,将弹道优化问题转化为多目标优化问题;基于对指标函数之间依赖性的分析,在求解过程中将多目标优化分解为参数层和指标层优化两部分,采用微粒群算法对其进行分层优化求解。仿真研究表明,该优化算法能够对弹道进行有效优化。

关键词:弹道优化;多重打靶算法;微粒群算法;多目标优化

收稿日期:2014-02-11

基金项目:航空科学

作者简介:邵雷(1982- ),男,讲师,博士,研究方向为非线性控制、飞行器制导与控制。E-mail:shaoleijing@126.com。

中图分类号:V412.4文献标识码:A

Midcourse Guidance Trajectory Optimization Based on

Particle Swarm Optimization Algorithm

SHAO Lei1,LEI Hu-min1,ZHANG Jian-xin2,ZHAO Zong-bao1

(1.College of Air and Missile Defense,Air Force Engineering University,Xi’an 710051,China;

2.The Military Representative Office at 786 Factory of PLA,Xi’an 710043,China)

Abstract:To achieve the maximum kill probability in the target interception,the multiple shooting algorithm and the particle swarm optimization were combined,and a particle swarm optimization(PSO) algorithm was presented based on optimization algorithm of midcourse guidance trajectory.According to the idea of the multiple shooting algorithm,the proposed algorithm transformed the trajectory optimization to a multi-objective optimization problem by means of state space decomposition and endpoint constrain based on performance index.The multi-objective optimization problem was transformed to the optimization of parameter and performance index by analyzing the reliability between the two,and the PSO was employed to deal with the problem.The simulation result shows that the trajectory can be effectively optimized by the proposed algorithm.

Key words:trajectory optimization;multiple shooting algorithm;particle swarm optimization;multi-objective optimization

在防空作战中,飞行弹道是拦截武器综合性能的反应,决定了拦截武器能否命中目标。弹道优化是拦截武器设计的重要内容之一,沿着合理的弹道飞行有利于提高拦截武器的飞行品质,达到有效命中目标的目的。

弹道优化问题实际是根据给定的战技指标建立拦截武器运动方程,选择主要设计参数,构造性能泛函,并考虑在内点和边值条件约束的情况下,运用现代控制理论求解最优参数形成相应的飞行弹道。……