Computing the Minimum-Time Interception of a Moving Target

IF 1.6 3区 数学 Q2 MATHEMATICS, APPLIED Journal of Optimization Theory and Applications Pub Date : 2024-07-06 DOI:10.1007/s10957-024-02487-2
Maksim Buzikov
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Abstract

In this study, we propose an algorithmic framework for solving a class of optimal control problems. This class is associated with the minimum-time interception of moving target problems, where a plant with a given state equation must approach a moving target whose trajectory is known a priori. Our framework employs an analytical description of the distance from an arbitrary point to the reachable set of the plant. The proposed algorithm is always convergent and cannot be improved without losing the guarantee of its convergence to the correct solution for arbitrary Lipschitz continuous trajectories of the moving target. In practice, it is difficult to obtain an analytical description of the distance to the reachable set for the sophisticated state equation of the plant. Nevertheless, it was shown that the distance can be obtained for some widely used models, such as the Dubins car, in an explicit form. Finally, we illustrate the generality and effectiveness of the proposed framework for simple motions and the Dubins model.

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计算拦截移动目标的最短时间
在本研究中,我们提出了一种求解最优控制问题的算法框架。这类问题与移动目标的最短时间拦截问题有关,在这类问题中,具有给定状态方程的植物必须接近移动目标,而移动目标的轨迹是先验已知的。我们的框架采用了对任意点到工厂可到达集的距离的分析描述。对于移动目标的任意 Lipschitz 连续轨迹,所提出的算法始终是收敛的,如果不保证收敛到正确解,则无法改进。在实践中,对于复杂的工厂状态方程,很难对到达可到达集的距离进行分析描述。不过,对于一些广泛使用的模型(如杜宾斯小车),我们已经证明可以以明确的形式获得该距离。最后,我们说明了针对简单运动和杜宾斯模型提出的框架的通用性和有效性。
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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
149
审稿时长
9.9 months
期刊介绍: The Journal of Optimization Theory and Applications is devoted to the publication of carefully selected regular papers, invited papers, survey papers, technical notes, book notices, and forums that cover mathematical optimization techniques and their applications to science and engineering. Typical theoretical areas include linear, nonlinear, mathematical, and dynamic programming. Among the areas of application covered are mathematical economics, mathematical physics and biology, and aerospace, chemical, civil, electrical, and mechanical engineering.
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