4.6 Article

Event-Based Tracking Consensus for Multiagent Systems With Volatile Control Gain

期刊

IEEE TRANSACTIONS ON CYBERNETICS
卷 52, 期 7, 页码 6603-6614

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2020.3027039

关键词

Control systems; Protocols; Couplings; Switches; Multi-agent systems; Network topology; Topology; Consensus; event-triggered control; intermittent control; multiagent; time-varying control

资金

  1. National Natural Science Foundation of China [71774070]
  2. Jiangsu University [14JDG078]

向作者/读者索取更多资源

This work investigates the tracking consensus problem of multiagent systems over directed networks, and proposes event-based consensus protocols. By using an extended differential inequality, criteria for tracking consensus under time- and state-dependent triggering conditions are constructed. It is proved that the time average of the control gain, together with the agent dynamics, network topology, and triggering conditions, governs the consensus despite the fluctuation of control gain.
This work investigates the tracking consensus problem of multiagent systems over directed networks, where the control gains follow certain volatile patterns. Some event-based consensus protocols are formulated so as to reduce the redundant execution of control. By using an extended differential inequality with a time-dependent coefficient, criteria for tracking consensus under time- and state-dependent triggering conditions are constructed, respectively. It is proved that the time average of the control gain, together with the agent dynamics, network topology, and triggering conditions, governs the consensus despite the fluctuation of control gain. The derived theorem can be utilized to ensure consensus with intermittent strategies aiming to lessen the burden in communications, including aperiodic on-off control with periodic perturbation and pulse-modulated on-off control. Unlike existing works, the requirement of a positive lower bound of control ratios is removed and, thus, a wide range of control gain patterns is possible, signifying higher flexibility in intermittent policy design. Finally, numerical examples are provided to further illustrate the theoretical results.

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