航空学报 > 2015, Vol. 36 Issue (6): 2037-2046   doi: 10.7527/S1000-6893.2014.0359

基于控制变量参数化的主动反拦截突防最优控制计算方法

王芳1,2, 林涛1,2, 张克1   

  1. 1. 北京机电工程研究所, 北京 100074;
    2. 哈尔滨工业大学 航天学院, 哈尔滨 150001
  • 收稿日期:2014-06-23 修回日期:2014-07-29 出版日期:2015-06-15 发布日期:2015-01-07
  • 通讯作者: 王芳 Tel.: 010-68741246 E-mail: wangfang_hit@163.com E-mail:wangfang_hit@163.com
  • 作者简介:王芳 女, 博士研究生。主要研究方向: 飞行器总体设计与制导控制。 Tel: 010-68741246 E-mail: wangfang_hit@163.com

Control variable parameterization-based computational method for optimal control of initiative anti-interception penetration

WANG Fang1,2, LIN Tao1,2, ZHANG Ke1   

  1. 1. Beijing Electro-mechanical Engineering Institute, Beijing 100074, China;
    2. School of Astronautics, Harbin Institute of Technology, Harbin 150001, China
  • Received:2014-06-23 Revised:2014-07-29 Online:2015-06-15 Published:2015-01-07

摘要:

针对由于敌防空系统防御能力不断提高所带来的进攻导弹突防难题,提出主动反拦截突防(IAIP)的概念,以弥补传统机动突防仅考虑进攻导弹的逃逸而忽略其攻击任务的缺陷。根据IAIP制导的内涵,在综合考虑目标的机动性能、拦截导弹末段的拦截特性及进攻导弹的控制系统性能的基础上,建立进攻导弹-目标-拦截导弹的三体运动模型。将突防制导指令的设计等效为最优控制的求解,其中突防指令为实现燃料最省目标的最优解,进攻导弹的过载、拦截导弹的脱靶量、进攻导弹的攻击角、打击精度和突防后的视线角,分别为控制约束、路径约束和末端约束。借鉴控制变量参数化(CVP)方法将最优控制问题转化为非线性数学规划问题,并将路径约束离散化后采用序列二次规划(SQP)算法得到突防时机给定条件下制导指令的数值解。提出基于CVP的混合遗传算法(CVP-GA),用于求解最优突防时机及制导指令。仿真结果显示,采用IAIP最优控制算法的进攻导弹在成功突防后的打击精度仍可满足任务要求,且其燃料消耗相对于传统串联式突防方法降低了23.7%,验证了该方法的有效性及优越性。

关键词: 主动反拦截突防, 最优控制, 控制变量参数化, 路径约束离散化, 遗传算法

Abstract:

To solve the problem caused by experiencing increases in defense capability of enemy antiaircraft system, the concept of initiative anti-interception penetration (IAIP) is proposed, to make up for the defects of the traditional penetration that only takes escape into account, while ignoring attack mission. According to the connotation of IAIP guidance, and considering the maneuver performance of target, terminal intercepting characteristics of interceptor missile and control system performance of attack missile, the three-body motion model, named attacker-target-interceptor, has been established, and the design of penetration guided command has been equivalent to solving nonlinear optimal control problem, where the penetration command is the solution of optimal control for minimizing fuel consumption, overload of attacker, miss distance of interceptor, attack angle, hit precision and angle of sight after penetration of attacker, are control constraint, path constraint and terminal constraint. After the optimal control problem is transformed into nonlinear integer programming model based on control variable parameterization (CVP) method and the continuous path constraint is simulated by scatter point, sequential quadratic program (SQP) algorithm is used to get the numerical solution of guidance commands under the condition of penetration occasion is given. An hydride genetic algorithm based on CVP (CVP-GA), is proposed to obtain the optimal penetration occasion and guided command. Simulation results show that hit accuracy of attacker used the optimal control of IAIP can still meet the mission requirements after successful penetration its fuel consumption is reduced by 23.7% compared with the traditional tandem penetration method, demonstrating the efficiency and superiority of the proposed method.

Key words: initiative anti-interception penetration, optimal control, control variable parameterization, path constraint discretization, genetic algorithm

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