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A Fully Distributed Protocol with an Event-Triggered Communication Strategy for Second-Order Multi-Agent Systems

Tao Li1, Quan Qiu1, Chunjiang Zhao2

  • 1Beijing Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China.

Sensors (Basel, Switzerland)
|July 2, 2021
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Summary
This summary is machine-generated.

This study introduces an event-triggered communication strategy for multi-agent systems (MASs) with nonlinear dynamics. The novel approach conserves communication resources and ensures leader-following consensus without Zeno behavior.

Keywords:
event-triggerleader-following consensusmulti-agent systemsnonlinear dynamics

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Area of Science:

  • Control Theory
  • Robotics
  • Networked Systems

Background:

  • Multi-agent systems (MASs) often face communication resource limitations.
  • Continuous communication signals in lead-follower MASs can be inefficient.
  • Existing methods may rely on centralized information or be susceptible to noise.

Purpose of the Study:

  • To propose a novel event-triggered communication mechanism for second-order MASs with nonlinear dynamics.
  • To enhance communication efficiency by avoiding continuous signals and reducing resource usage.
  • To ensure robust leader-following consensus despite communication constraints and noise.

Main Methods:

  • Development of an event-triggered communication strategy with adaptive thresholds.
  • Design of a network protocol incorporating updated coupling gains and relative positions.
  • Utilization of a Lyapunov-Krasovskii functional for rigorous stability analysis.

Main Results:

  • Achieved leader-following consensus in second-order nonlinear MASs.
  • Demonstrated the absence of Zeno behavior in the proposed communication strategy.
  • Verified the protocol's effectiveness through numerical simulations.

Conclusions:

  • The proposed event-triggered communication mechanism effectively achieves consensus in MASs.
  • The strategy conserves communication resources and mitigates the impact of noise.
  • This approach offers a robust solution for decentralized control in networked systems.