Target–Attackers–Defenders Linear–Quadratic Exponential Stochastic Differential Games With Distributed Control

IF 10.5 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2025-01-06 DOI:10.1109/TCYB.2024.3508694
Guilu Li;Jianan Wang;Fuxiang Liu;Fang Deng
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Abstract

This article investigates stochastic differential games involving multiple attackers, defenders, and a single target, with their interactions defined by a distributed topology. By leveraging principles of topological graph theory, a distributed design strategy is developed that operates without requiring global information, thereby minimizing system coupling. Additionally, this study extends the analysis to incorporate stochastic elements into the target-attackers–defenders games, moving beyond the scope of deterministic differential games. Using the direct method of completing the square and the Radon-Nikodym derivative, we derive optimal distributed control strategies for two scenarios: one where the target follows a predefined trajectory and another where it has free maneuverability. In both scenarios, our research demonstrates the effectiveness of the designed control strategies in driving the system toward a Nash equilibrium. Notably, our algorithm eliminates the need to solve the coupled Hamilton-Jacobi equation, significantly reducing computational complexity. To validate the effectiveness of the proposed control strategies, numerical simulations are presented in this article.
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目标-攻击者-防御者分布控制线性-二次指数随机微分对策
本文研究涉及多个攻击者、防御者和单个目标的随机微分博弈,它们的交互由分布式拓扑定义。通过利用拓扑图理论的原理,开发了一种不需要全局信息的分布式设计策略,从而最大限度地减少了系统耦合。此外,本研究扩展了分析,将随机元素纳入目标-攻击者-防御者博弈,超越了确定性微分博弈的范围。利用直接方格补全法和Radon-Nikodym导数,我们推导了两种情况下的最优分布式控制策略:一种是目标遵循预定轨迹,另一种是目标具有自由机动。在这两种情况下,我们的研究证明了所设计的控制策略在推动系统走向纳什均衡方面的有效性。值得注意的是,我们的算法消除了求解耦合Hamilton-Jacobi方程的需要,大大降低了计算复杂度。为了验证所提出的控制策略的有效性,本文给出了数值仿真。
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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