[1]赵慧慧,纪志坚.距离划分下基于一致性协议的符号网络能控性[J].智能系统学报,2025,20(5):1178-1187.[doi:10.11992/tis.202405038]
ZHAO Huihui,JI Zhijian.Symbolic network controllability based on a consistency protocol under distance division[J].CAAI Transactions on Intelligent Systems,2025,20(5):1178-1187.[doi:10.11992/tis.202405038]
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ZHAO Huihui,JI Zhijian.Symbolic network controllability based on a consistency protocol under distance division[J].CAAI Transactions on Intelligent Systems,2025,20(5):1178-1187.[doi:10.11992/tis.202405038]
距离划分下基于一致性协议的符号网络能控性
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
20
期数:
2025年第5期
页码:
1178-1187
栏目:
学术论文—智能系统
出版日期:
2025-09-05
- Title:
- Symbolic network controllability based on a consistency protocol under distance division
- Keywords:
- multiagent network; distance division; undirected signed network; controllability; leader-follower framework; eigenvalue; eigenvector; control theory
- 分类号:
- TP273
- 摘要:
- 针对一般线性多智能体系统研究了符号网络的能控性。首先，聚焦2种不同的leader-follower模型，分析并描述了二者在表现形式上呈现出的差异。其次，基于上述模型，利用首次提出的距离划分这一工具，从网络拓扑的角度定量刻画了网络的能控子空间。进一步，受距离划分的启发，得到了系统K步可控的条件(K步可控是指控制信号在K步之内可达所有节点，K值等于系统的能控性指数)。特别地，针对密集网络(结构更为复杂)拓扑，给出了一种计算系统K值的算法，该算法从图论视角入手，通过遍历和删减边的操作，避免了传统方法中通过复杂的矩阵计算才得到K值的问题，并为领导者的选择提供了方法。最后，通过例子验证了算法的有效性。
- Abstract:
- The controllability of symbolic networks in general linear multiagent systems is explored in this study. First, two distinct leader-follower models are analyzed, highlighting and clarifying the differences in their expressions. Next, building on the above-mentioned models, the controllable subspace of the network is quantitatively described from the perspective of network topology, utilizing the distance division tool introduced here for the first time. Inspired by distance division, conditions for K-controllability were obtained (K-controllability means that the control signal can reach all nodes within K steps, where K corresponds to the system’s controllability index). For dense network topologies with complex structures, a novel algorithm is proposed for calculating the system’s K value. By adopting a graph theory approach, the algorithm leverages operations such as traversing and trimming edges of the topology graph. This approach circumvents the need for complex matrix calculations used in traditional methods while also providing a method for leader selection. Finally, the validity of the algorithm is demonstrated through practical examples.
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备注/Memo
收稿日期:2024-5-28。
基金项目:国家自然科学基金项目（62373205, 62033007）；山东省泰山学者特聘教授人才支持计划项目（tstp20230624, ts20190930）；山东省泰山学者攀登计划资助课题；青岛大学系统科学+联合研究计划项目（XT2024101）.
作者简介:赵慧慧，硕士研究生，主要研究方向为群体智能。E-mail：zhaohuihui2000@163.com。;纪志坚，教授，博士生导师，博士。主要研究方向为群体智能系统复杂性分析与调控、多智能体网络系统、切换与混杂系统和多机器人系统的分布式协同控制。主持国家自然科学基金项目5项、国家自然科学基金重点项目子课题1项，获得英国皇家学会牛顿国际学者基金会(Newton international fellowship)王宽诚国际学者基金。发表学术论文180余篇。E-mail：jizhijian@pku.or.cn。
通讯作者:纪志坚. E-mail：jizhijian@pku.or.cn
更新日期/Last Update:
2025-09-05