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Quasi-exact dynamic average consensus under asynchronous communication and symmetric delays.

Rodrigo Aldana-López1, Rosario Aragüés2, Carlos Sagüés2

  • 1Intel Tecnología de México, Intel Labs, Av. del Bosque 1001, 45019, Zapopan, Jalisco, Mexico.

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Summary

This study presents a novel distributed algorithm for dynamic average consensus using high-order sliding modes. The method achieves accurate average computation even with asynchronous communication and time delays, enhancing network robustness.

Keywords:
Asynchronous communicationDynamic average consensusDynamic average trackingSliding-modesSymmetric delays

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Area of Science:

  • Control Systems
  • Distributed Computing
  • Networked Systems

Background:

  • Distributed systems require computing averages of time-varying signals across networks.
  • Realistic networks face challenges like asynchronous communication and time-varying delays.

Purpose of the Study:

  • To develop a robust distributed algorithm for dynamic average consensus.
  • To address limitations of existing methods in asynchronous and delayed communication environments.

Main Methods:

  • Utilizing high-order sliding modes for distributed computation.
  • Designing an algorithm for agents communicating at asynchronous discrete-time instants.
  • Incorporating analysis of time-varying symmetric edge-wise delays.

Main Results:

  • The proposed algorithm achieves quasi-exact convergence to the dynamic average signal.
  • Demonstrated reduced chattering and improved robustness under asynchronous discrete-time communication.
  • Formal convergence analysis and numerical experiments validate the algorithm's performance.

Conclusions:

  • High-order sliding modes offer an effective approach for dynamic average consensus in challenging network conditions.
  • The algorithm provides a significant improvement over existing methods for asynchronous and delayed networks.
  • This work advances distributed computation for networked systems with dynamic and uncertain parameters.