基于时间约束集的多弹道式飞行器避撞发射时间规划
收稿日期: 2014-08-14
修回日期: 2014-12-17
网络出版日期: 2014-12-23
基金资助
国家自然科学基金 (61350010)
Multiple ballistic flight vehicles' launch time planning for collision avoidance based on time constraint set
Received date: 2014-08-14
Revised date: 2014-12-17
Online published: 2014-12-23
Supported by
National Natural Science Foundation of China (61350010)
提出了通过调整发射时间解决多弹道式飞行器飞行避撞问题的算法框架,在该框架内针对多弹道式飞行器协同打击时是否发生飞行碰撞提出了检验算法,对于飞行器碰撞规避问题建立发射时间约束集模型,约束集由飞行器间发生碰撞的发射时间间隔约束构成。在该时间约束集的基础上建立以多弹道式飞行器同时打击为优化目标、含有不等于号表达式时间约束的优化问题,并通过"Big-M"法将该问题转化为非线性规划问题的标准形式,再利用序列二次规划(SQP)算法进行求解。该框架将发射时间调整问题转化为最优化规划问题,降低了传统遍历性发射时间调整算法的计算复杂度。基于MATLAB平台环境对所提模型及规划算法进行了仿真,验证了所提算法的合理性与有效性,同时具有较高的计算效率。
张思宇 , 于剑桥 , 李品磊 . 基于时间约束集的多弹道式飞行器避撞发射时间规划[J]. 航空学报, 2015 , 36(7) : 2391 -2399 . DOI: 10.7527/S1000-6893.2014.0352
An algorithm framework is presented to solve multiple ballistic flight vehicles' collision avoidance problem by adjusting their launch time. A collision detection algorithm is proposed in the framework for detecting whether there is flight collision or not in multiple ballistic flight vehicles' cooperative attack, and a launch time constraint set model is built in order to solve the collision avoidance problem. The constraint set is constituted by the launch time interval constraints of the flight vehicles in collision. On the foundation of this time constraint set, an optimization problem which regards multiple ballistic flight vehicles' arriving simultaneously as the optimization goals and includes the expression with the sign of inequality constraints is built, and then the "Big-M" method is improved to transform the problem to standard form of nonlinear programming problem which can be solved by sequential quadratic programming (SQP). The method framework transforms the launch time adjusting problem to an optimization planning problem and has reduced the computational complexity compared with the traditional ergodic launch time planning algorithms. With MATLAB platform, simulations have proved the rationality and effectiveness of the proposed method and the method has high computation efficiency.
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