动态任务切换下多智能体运动目标防御系统的竞争与合作

IF 8.6 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Haiyan Zhao;Rongxin Cui;Weisheng Yan;Lepeng Chen
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引用次数: 0

摘要

在本研究中,我们提出了一种竞争与合作方式的多智能体系统(MAS)的动态任务切换移动目标防御协调协议。该协议包括三个部分。首先,我们在改进的k-赢者通吃(k-WTA)框架内设计了一个基于距离的竞争分布式决策算法。该算法为每个agent生成动态的二进制任务驱动信号,实现任意比例的MAS近乎最优在线分组。其次,我们引入了一种采用共享决策机制并利用反馈线性化的协作策略,该策略不需要全局位置信息。该策略生成运动规划信号,协调agent的动作,实现跟踪、捕获、拦截等整体合作行为。最后,我们结合基于二阶非线性动力学的自适应滑模技术来增强对干扰的鲁棒性,确保闭环系统的一致最终有界性(UUB)。此外,对轮式移动机器人(WMRs)的仿真和实验验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Competition and Cooperation of Multiagent System for Moving Target Defense With Dynamic Task-Switching
In this study, we present a coordinated protocol for a multiagent system (MAS) in competitive and cooperative manners for moving target defense with dynamic task-switching. The protocol comprises three components. First, we design a distance-based competitive distributed decision algorithm within an improved k-Winner-Take-All (k-WTA) framework. This algorithm generates dynamic binary task-driven signals for each agent, enabling near-optimal online grouping of MAS with arbitrary proportions. Second, we introduce a cooperative strategy that employs a shared decision-making mechanism and utilizes feedback linearization without global position information. This strategy generates motion planning signals to coordinate the agents’ actions, achieving overall cooperative behaviors such as tracking, capturing, and intercepting. Finally, we incorporate an adaptive sliding mode technique based on second-order nonlinear dynamics to enhance robustness against disturbances, ensuring uniformly ultimately boundedness (UUB) of the closed-loop system. In addition, simulations and experiments with wheeled mobile robots (WMRs) validate the effectiveness of our method.
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来源期刊
IEEE Transactions on Systems Man Cybernetics-Systems
IEEE Transactions on Systems Man Cybernetics-Systems AUTOMATION & CONTROL SYSTEMS-COMPUTER SCIENCE, CYBERNETICS
CiteScore
18.50
自引率
11.50%
发文量
812
审稿时长
6 months
期刊介绍: The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.
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