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A Game-Based Guidance Law Against Higher-Speed Maneuvering Penetrator Using Model Predictive Method

机译:基于模型预测方法的基于速度的机动机动侵彻制导律

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To intercept higher-speed maneuvering target, interception modes are analyzed and head-on posture with maneuverable advantage of interceptor is determined to be the prerequisite. A differential game-based guidance law is proposed under the framework of model predictive control. Gradient-iteration algorithm subject to input constraints is implemented for on-line optimization with respect to a composite objective functional consisting of line-of-sight rate and fuel consumption. Algorithm's effectiveness for obtaining saddle points of the game is derived on some preconditions. The numerical simulation results show the importance of choosing suitable cost weights and validate the performance of the guidance law. The accessible zone against higher-speed maneuvering penetrator involving varying initial conditions is computed by assuming the other vehicle moves optimally.
机译:为了拦截高速机动目标,分析了拦截方式,确定了具有拦截器可操纵优势的迎头姿势是前提。在模型预测控制的框架下,提出了一种基于博弈的差分制导律。实施受输入约束的梯度迭代算法,以针对由视线速率和燃油消耗组成的复合目标函数进行在线优化。在某些前提条件下,得出了算法获得游戏鞍点的有效性。数值模拟结果表明选择合适的成本权重并验证指导律的性能的重要性。通过假定其他车辆最佳运动来计算涉及变化初始条件的高速机动穿透器的可到达区域。

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