4.7 Article

Fixed-Time Average Consensus of Nonlinear Delayed MASs Under Switching Topologies: An Event-Based Triggering Approach

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2021.3051156

关键词

Topology; Switches; Delays; Convergence; Uncertainty; Sun; Multi-agent systems; Event-based control; fixed-time average consensus; nonlinear multiagent systems (MASs); switching topologies

资金

  1. National Key Research and Development Program of China [2018AAA0101400]
  2. National Natural Science Foundation of China [61921004, 62033010, 62033009]
  3. Natural Science Foundation of Jiangsu Province of China [BK20202006]
  4. National Postdoctoral Program for Innovative Talents [BX20200081]
  5. China Postdoctoral Science Foundation [2020TQ0041]
  6. Jiangsu Planned Projects for Postdoctoral Research Funds [2020Z081]

向作者/读者索取更多资源

This article addresses the fixed-time average consensus problem of nonlinear multiagent systems subject to various challenges, such as input delay, external disturbances, and switching topologies. An event-based control strategy is proposed to tackle this problem effectively, considering factors like nonlinear dynamics, external disturbances, and intermittent communication. The proposed approach reduces resource consumption significantly compared to continuous monitoring methods.
This article addresses the fixed-time average consensus problem of nonlinear multiagent systems (MASs) subject to input delay, external disturbances, and switching topologies. Different from the finite-time convergence, the convergence time of the fixed-time convergence is independent of initial conditions. Then, an event-based control strategy is presented to reach the fixed-time average consensus under switching topologies and intermittent communication. Because the nonlinear dynamics, external disturbances, switching topologies, and triggering condition for intermittent communication are considered, the fixed-time consensus problem is more challenging under the event-based control than under the continuous-time control. Besides, a new measurement error is designed based on the hyperbolic tangent function to avoid Zeno behavior. Furthermore, an improved triggering function is designed to avoid continuous monitoring. Hence, resource consumption is reduced significantly. Finally, the effectiveness of the algorithms is validated by three simulation examples.

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