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Fast consensus in a large-scale multi-agent system with directed graphs using time-delayed measurements.

Adrián Ramírez1,2, Rifat Sipahi2, Sabine Mondié3

  • 1Division of Applied Mathematics, IPICYT, San Luis Potosí, SLP 78216, México.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|July 23, 2019
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Summary
This summary is machine-generated.

This study enhances consensus-reaching in multi-agent systems (MAS) by analytically tuning controllers with delayed measurements. This approach handles complex eigenvalues, extending analysis to directed graphs beyond symmetric networks.

Keywords:
delay-based controlfast consensusmulti-agent systemspole placementtime delay systems

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Area of Science:

  • Control Theory
  • Networked Systems
  • Robotics

Background:

  • Consensus-reaching in multi-agent systems (MAS) is crucial for coordinated behavior.
  • Standard controller tuning often relies on current measurements, which can be suboptimal.
  • Existing methods for MAS controller tuning are often limited to real eigenvalues and symmetric graphs.

Purpose of the Study:

  • To develop an analytical approach for tuning controllers in MAS with delayed measurements.
  • To extend controller tuning methods beyond real eigenvalues to complex eigenvalues.
  • To enable the analysis of MAS under directed graphs.

Main Methods:

  • An analytic geometry approach is proposed for controller tuning.
  • The method focuses on the complex eigenvalues of the graph Laplacian.
  • Delayed measurements are incorporated into the controller design.

Main Results:

  • The proposed method successfully tunes controllers for MAS with delayed measurements.
  • Tuning for complex eigenvalues is achieved, broadening applicability.
  • The approach is validated for MAS operating under directed graphs.

Conclusions:

  • Delayed measurements can be beneficial for controller tuning in MAS.
  • The analytic geometry approach offers a significant advancement for MAS analysis.
  • This work extends the understanding of consensus-reaching in complex network topologies.