Article
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A Distributed Algorithm for Reaching Average Consensus in Unbalanced Tree Networks
Version 1
: Received: 16 August 2024 / Approved: 19 August 2024 / Online: 19 August 2024 (10:18:46 CEST)
How to cite: Parlangeli, G. A Distributed Algorithm for Reaching Average Consensus in Unbalanced Tree Networks. Preprints 2024, 2024081310. https://doi.org/10.20944/preprints202408.1310.v1 Parlangeli, G. A Distributed Algorithm for Reaching Average Consensus in Unbalanced Tree Networks. Preprints 2024, 2024081310. https://doi.org/10.20944/preprints202408.1310.v1
Abstract
In this paper, a distributed algorithm for reaching average consensus is proposed for multi-agent systems with tree communication graph, when the edge weight distribution is unbalanced. First, the problem is introduced as a key topic of core algorithms for several modern scenarios. Then, the relative solution is proposed as a finite-time algorithm, which can be included in any application as a preliminary setup routine, and it is well-suited to be integrated with other adaptive setup routines, thus making the proposed solution useful in several practical applications. A special focus is devoted to the integration of the proposed method with a recent Laplacian eigenvalue allocation algorithm, and the implementation of the overall approach in a wireless sensor network framework. Finally, a worked example is provided, showing the significance of this approach for reaching a more precise average consensus in uncertain scenarios.
Keywords
Laplacian eigenvectors; Perron vector; average consensus problems
Subject
Engineering, Control and Systems Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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