期刊
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
卷 61, 期 2, 页码 499-511出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCSI.2013.2268091
关键词
Consensus tracking; multi-agent system; nonsingular M-matrix; switching directed topology; synchronization
资金
- Hong Kong Research Grants Council under the GRF [CityU 1114/11E]
- National Nature Science Foundation of China [61225013, 61104145]
- Natural Science Foundation of Jiangsu Province of China [BK2011581]
- Research Fund for the Doctoral Program of Higher Education of China [20110092120024]
- Information Processing and Automation Technology Prior Discipline of Zhejiang Province-Open Research Foundation [20120801, 20120802]
- Fundamental Research Funds for the Central Universities of China
Distributed consensus tracking is addressed in this paper for multi-agent systems with Lipschitz-type node dynamics. The main contribution of this work is solving the consensus tracking problem without the assumption that the topology among followers is strongly connected and fixed. By using tools from M-matrix theory, a class of consensus tracking protocols based only on the relative states among neighboring agents is designed. By appropriately constructing Lyapunov function, it is proved that consensus tracking in the closed-loop multi-agent systems with a fixed topology having a directed spanning tree can be achieved if the feedback gain matrix and the coupling strength are suitably selected. Furthermore, with the assumption that each possible topology contains a directed spanning tree, it is theoretically shown that consensus tracking under switching directed topologies can be achieved if the control parameters are suitably selected and the dwell time is larger than a positive threshold. The results are then extended to the case where the communication topology contains a directed spanning tree only frequently as the system evolves with time. Finally, some numerical simulations are given to verify the theoretical analysis.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据