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This study investigates the consensus problem of second-order multi-agent systems subject to time-varying interval-like delays. The notion of consensus is extended to networks containing antagonistic interactions modeled by negative weights on the communication graph. A unified framework is established to address both the stationary and dynamic consensus issues in sampled-data settings. Using the reciprocally convex approach, a sufficient condition for consensus is derived in terms of matrix inequalities. Numerical examples are provided to illustrate the effectiveness of the proposed result.


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Consensus of Second-Order Multi-Agent Systems with Time-Varying Delays and Antagonistic Interactions

Show Author's information Bo HouFuchun SunHongbo Li( )Guangbin Liu
State Key Laboratory on Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China.
High-Tech Institute of Xi’an, Xi’an 710025, China

Abstract

This study investigates the consensus problem of second-order multi-agent systems subject to time-varying interval-like delays. The notion of consensus is extended to networks containing antagonistic interactions modeled by negative weights on the communication graph. A unified framework is established to address both the stationary and dynamic consensus issues in sampled-data settings. Using the reciprocally convex approach, a sufficient condition for consensus is derived in terms of matrix inequalities. Numerical examples are provided to illustrate the effectiveness of the proposed result.

Keywords: consensus, multi-agent systems, second-order, cooperation and competition

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Publication history

Received: 25 November 2014
Revised: 05 January 2015
Accepted: 25 January 2015
Published: 23 April 2015
Issue date: April 2015

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© The author(s) 2015

Acknowledgements

This research was jointly supported by the Specialized Research Fund for the Doctoral Program of Higher Education (No. 20110002110015), the National Key Basic Research and Development (973) Program of China (No. 2012CB821206), the National National Science Foundation of China (Nos. 61473161, 61174069, and 51374082), and Tsinghua University Initiative Scientific Research Program.

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