Decentralized finite-time adaptive consensus of multiagent systems with fixed and switching network topologies

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• 作者：Zhizhong Tu^a ; ^b ; ^{tuzhizhongsina@163.com}Author Vitae ; Hui Yu^a ; ^{yuhui@ctgu.edu.cn}Author Vitae ; Xiaohua Xia^b ; ^{xxia@up.ac.za}Author Vitae
• 关键词：Multiagent system ; Unknown nonlinear dynamics ; Finite-time consensus ; Finite-time parameter convergence
• 刊名：Neurocomputing
• 出版年：2017
• 出版时间：5 January 2017
• 年：2017
• 卷：219
• 期：Complete
• 页码：59-67
• 全文大小：1254 K
• 卷排序：219

文摘

In this paper, finite-time adaptive consensus problem is investigated for first-order multiagent systems with unknown nonlinear dynamics. Linearly parameterized method is introduced to model unknown nonlinear dynamics of the systems. By only utilizing the local relative position state information between each agent and its neighbors, decentralized finite-time adaptive consensus algorithms are presented with directed fixed and switching network topologies which satisfy detailed balance condition. Based on classical Lyapunov analysis techniques, both finite-time stability and finite-time parameter convergence are guaranteed by making use of the proposed control algorithms. Finally, the results in Simulations part are presented to validate our main results.