弹道导弹机动能力受限反拦截博弈弹道优化方法
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南京理工大学

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TJ765.3

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水下信息与控制科学技术实验室基金资助项目(2022-JCJQ-LB-030-09)


Ballistic missile maneuverability limited anti-interception game trajectory optimization method
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    摘要:

    针对突防-拦截过程中存在的机动能力受限问题,提出了一种机动能力受限下基于自适应动态规划的博弈弹道优化策略求解方法。通过建立仿射非线性微分博弈模型,并考虑到机动能力受限约束,设计了含积分形式的控制能量项的性能指标函数;基于微分博弈理论推导了博弈鞍点控制策略,并基于自适应动态规划算法设计一个评价网络对微分博弈策略进行近似逼近求解,给出了评价神经网络权值自适应更新律并对其稳定性进行了推导证明。仿真结果表明,所提出的策略求解方法能够在机动能力受限的情况下实现反拦截效果,精确打击敌方目标。

    Abstract:

    Aiming at the problem of maneuverability limitation in the process of penetration and interception, a game trajectory optimization strategy solution based on adaptive dynamic programming is proposed. By establishing an affine nonlinear differential game model and considering the limited maneuverability, the performance index function of the control energy term with integral form was designed. The saddle point control strategy of the game was derived based on the differential game theory, and an evaluation network was designed based on the adaptive dynamic programming algorithm to approximate the solution of the differential game strategy. The weight adaptive updating law of the evaluation neural network was given and its stability was proved. Simulation results show that the proposed strategy solving method can achieve anti-interception effect and accurately strike enemy targets under the circumstance of limited maneuverability.

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  • 收稿日期:2025-03-13
  • 最后修改日期:2025-05-26
  • 录用日期:2025-05-27
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