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Adaptive connectivity control in networked multi-agent systems: A distributed approach.

Marko Križmančić1, Stjepan Bogdan1

  • 1University of Zagreb Faculty of Electrical Engineering and Computing, Zagreb, Croatia.

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This study introduces a distributed method to monitor and control communication networks in multi-agent systems. It enhances connectivity and energy efficiency by dynamically adjusting network links, ensuring robust performance.

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Area of Science:

  • Multi-agent systems
  • Network science
  • Control theory

Background:

  • Effective communication is vital for cooperative networked multi-agent systems.
  • Current methods lack dynamic monitoring and adjustment of communication topologies for balancing connectivity and energy efficiency.

Purpose of the Study:

  • To propose a distributed approach for estimating and controlling system connectivity in multi-agent systems.
  • To address the gap in dynamically managing communication topologies for optimal performance.

Main Methods:

  • A modified consensus protocol for distributed estimation of a global weighted adjacency matrix.
  • Utilizing algebraic connectivity (the second smallest eigenvalue of the graph Laplacian) to measure system connectivity.
  • An adaptive mechanism to expedite consensus convergence and an analytical method for connectivity control using Fiedler vector approximation.

Main Results:

  • The proposed method effectively estimates and tracks algebraic connectivity in dynamic multi-agent systems.
  • Demonstrated robust connectivity maintenance against external disturbances and agent failures.
  • Identified and eliminated non-contributory links, improving long-term energy efficiency.

Conclusions:

  • The developed distributed approach enhances communication efficiency and robustness in cooperative networked multi-agent systems.
  • The strategy offers practical utility for real-world applications requiring dynamic network management.
  • This work provides a foundation for more intelligent and adaptive multi-agent communication strategies.