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在分数阶多智能体系统中达成共识:针对拜占庭攻击的代数方法

Securing consensus in fractional-order multi-agent systems: Algebraic approaches against Byzantine attacks.

作者信息

Zhong Yubin, Khan Asad, Javeed Muhammad Awais, Raza Hassan, Hassan Waqar Ul, Niazi Azmat Ullah Khan, Mehmood Muhammad Usman

机构信息

School of Mathematics and Information Science, Guangzhou University, Guangzhou 510006, PR China.

Metaverse Research Institute, School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou 510006, PR China.

出版信息

Heliyon. 2024 Nov 13;10(22):e40335. doi: 10.1016/j.heliyon.2024.e40335. eCollection 2024 Nov 30.

Abstract

This paper investigates the behavior of fractional-order nonlinear multi-agent systems subjected to Byzantine assaults, specifically focusing on the manipulations of both sensors and actuators. We employ weighted graphs, both directed and undirected, to illustrate the system's topology. Our methodology combines algebraic graph theory with fractional-order Lyapunov techniques to develop algebraic requirements for leader-following consensus, providing a robust framework for analyzing consensus dynamics in these complex systems. We present quantitative results demonstrating the effectiveness of our approach, including two numerical examples that validate the proposed requirements for consensus evaluation. Notably, our work highlights the novelty of using fractional-order systems to enhance resilience against adversarial conditions, contributing significantly to the field of multi-agent systems. By clarifying key terms and streamlining our language, we ensure accessibility for a broader audience while emphasizing the implications of our findings for real-world applications.

摘要

本文研究了遭受拜占庭攻击的分数阶非线性多智能体系统的行为,特别关注传感器和执行器的操纵。我们使用有向和无向加权图来说明系统的拓扑结构。我们的方法将代数图论与分数阶李雅普诺夫技术相结合,以制定领导者跟随一致性的代数要求,为分析这些复杂系统中的一致性动态提供了一个强大的框架。我们给出了定量结果,证明了我们方法的有效性,包括两个数值例子,验证了所提出的一致性评估要求。值得注意的是,我们的工作突出了使用分数阶系统来增强对对抗条件的弹性的新颖性,为多智能体系统领域做出了重大贡献。通过澄清关键术语并简化我们的语言,我们确保了更广泛的受众能够理解,同时强调了我们的发现对实际应用的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7148/11609225/caad777abe68/gr001.jpg

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