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Sampled-based consensus for nonlinear multi-agent systems with average graph.

Ying Cui1, Qingying Miao2, Wenbing Zhang3

  • 1Department of Mathematics, Fuyang Normal College, Fuyang 236032, China.

Chaos (Woodbury, N.Y.)
|October 3, 2019
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Summary
This summary is machine-generated.

This study introduces a novel sampled-based consensus protocol for nonlinear multiagent systems (MASs) with switching network topologies. The research ensures reliable consensus achievement by analyzing average graph properties and sampling periods.

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Area of Science:

  • Control Systems Engineering
  • Networked Systems Theory
  • Robotics and Automation

Background:

  • Multiagent systems (MASs) face challenges in achieving consensus due to dynamic network topologies and data sampling.
  • Switched topologies, especially among disconnected graphs, complicate the design of robust consensus protocols.

Purpose of the Study:

  • To develop a sampled-based consensus protocol for nonlinear MASs with switched topologies.
  • To establish a consensus criterion based on the average graph properties of the communication network.
  • To determine the maximum allowable sampling period for guaranteed consensus.

Main Methods:

  • Introduction of an "average graph" concept, weighted by switching frequency.
  • Development of a sampled-based consensus protocol.
  • Utilization of Lyapunov functions and contradiction theory to derive the consensus criterion.
  • Analysis of the Laplacian matrix of the average graph.

Main Results:

  • A consensus criterion is derived, requiring the average graph to contain a directed spanning tree.
  • The maximum allowable sampling period is determined based on the average graph's Laplacian matrix.
  • Theoretical results are validated through a numerical example.

Conclusions:

  • The proposed sampled-based consensus protocol effectively guarantees consensus in nonlinear MASs with switched topologies.
  • The average graph approach provides a robust framework for analyzing consensus under dynamic network conditions.
  • The derived consensus criterion and sampling period bound offer practical guidelines for designing such systems.