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Volume 2 Issue 3
Jul.  2015

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2015  >  2(3): 248-257
Zhaoxia Wang, Minrui Fei, Dajun Du and Min Zheng, "Decentralized Event-Triggered Average Consensus for Multi-Agent Systems in CPSs with Communication Constraints," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 3, pp. 248-257, 2015.
Citation: Zhaoxia Wang, Minrui Fei, Dajun Du and Min Zheng, "Decentralized Event-Triggered Average Consensus for Multi-Agent Systems in CPSs with Communication Constraints," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 3, pp. 248-257, 2015.
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Decentralized Event-Triggered Average Consensus for Multi-Agent Systems in CPSs with Communication Constraints

  • 1. Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China;

  • 2. School of Electrical Engineering and Automation, Qilu University of Technology, Jinan 250353, China;

  • 3. Shanghai Key Laboratoy of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China

Funds:

This work was supported by National Natural Science Foundation of China (61473182), National Key Scientific Instrument and Equipment Development Project (2012YQ15008703), Project of Science and Technology Commission of Shanghai Municipality (14JC1402200, 15JC1401900, 14ZR1414800), and Shanghai Rising-Star Program (13QA1401600).

    Abstract
  • The paper investigates decentralized event-triggered average consensus problem for multi-agent systems in cyberphysical systems (CPSs) with communication constraints. To reduce communication burden and improve the communication efficiency of multi-agent systems in CPSs, event-trigger is distributed at subsystem/agent level. A multi-agent system is then modeled as a reduced dimension hybrid system by taking into account decentralized event-triggered mechanism, communication delays and data dropouts within one framework. Some sufficient conditions for average consensus of each agent and an upper bound of communication delay and maximal allowable number of successive data dropouts (MANSD) are obtained, which can conveniently provide the relationship between the triggering parameters, communication constraints and the system stability. Specially, the quantitative relationship between the triggering parameters, MANSD and the system stability is derived. Finally, simulation results are given to illustrate the effectiveness of the proposed method.

     

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