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Cooperative pursuit strategy based on cascaded optimization of assignment and guidance
Automatica ( IF 4.8 ) Pub Date : 2024-08-03 , DOI: 10.1016/j.automatica.2024.111818
Hong Tao , Defu Lin , Tao Song , Hongyan Li

This paper proposes a cooperative pursuit strategy against a maneuvering target by introducing a cascaded optimization framework for assignment and guidance. The cooperative guidance algorithm, guaranteeing both encirclement and simultaneous attack constraints, is derived by optimizing the normal impact–direction and tangential impact–time control efforts, respectively. Then, by minimizing the performance index identical to the guidance loop, an assignment approach is proposed to allocate the desired impact direction and time for each pursuer. Since the assignment and guidance strategies share a unified optimization tenet in a cascaded manner, the proposed integrated cooperative method proves more efficient than the existing guidance-only methods. Theoretical analysis and numerical simulations are provided to demonstrate its advantages in synergy efficiency.

中文翻译:


基于分配引导级联优化的合作追击策略



本文通过引入用于分配和制导的级联优化框架,提出了针对机动目标的合作追击策略。通过分别优化法向冲击方向和切向冲击时间控制效果,导出了保证包围和同时攻击约束的协同制导算法。然后,通过最小化与引导环相同的性能指标,提出了一种分配方法,为每个追击者分配所需的撞击方向和时间。由于分配和引导策略以级联方式共享统一的优化原则,因此所提出的集成协作方法比现有的仅引导方法更有效。理论分析和数值模拟证明了其在协同效率方面的优势。
更新日期:2024-08-03
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