A Unified Framework Design for Finite-Time Bipartite Consensus of Multi-Agent Systems

Yu, Jiaju; Yu, Jianping; Zhang, Pengfei; Yang, Tingting; Chen, Xiurong

doi:10.1109/access.2021.3069337

Cited by 5 publications

(3 citation statements)

References 49 publications

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“…In that paper, the authors compare their approach with concurrent ones in regular bipartite graphs (not only in this topology) and identify that this approach outperforms other algorithms. As further seen in [55][56][57][58][59][60][61], the authors of these papers assume distributed consensus algorithms in either (only) bipartite, (only) regular, Ramanujan, triangular regular, strongly regular, distance regular, irregular, or disconnected graphs with regular bipartite components. Thus, these papers do not exactly address the same issue as we do in this paper.…”

Section: Distributed Consensus Algorithms In D-regular Bipartite Graphsmentioning

confidence: 99%

Distributed Average Consensus Algorithms in d-Regular Bipartite Graphs: Comparative Study

Kenyeres

2023

Future Internet

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Consensus-based data aggregation in d-regular bipartite graphs poses a challenging task for the scientific community since some of these algorithms diverge in this critical graph topology. Nevertheless, one can see a lack of scientific studies dealing with this topic in the literature. Motivated by our recent research concerned with this issue, we provide a comparative study of frequently applied consensus algorithms for distributed averaging in d-regular bipartite graphs in this paper. More specifically, we examine the performance of these algorithms with bounded execution in this topology in order to identify which algorithm can achieve the consensus despite no reconfiguration and find the best-performing algorithm in these graphs. In the experimental part, we apply the number of iterations required for consensus to evaluate the performance of the algorithms in randomly generated regular bipartite graphs with various connectivities and for three configurations of the applied stopping criterion, allowing us to identify the optimal distributed consensus algorithm for this graph topology. Moreover, the obtained experimental results presented in this paper are compared to other scientific manuscripts where the analyzed algorithms are examined in non-regular non-bipartite topologies.

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Section: Distributed Consensus Algorithms In D-regular Bipartite Graphsmentioning

confidence: 99%

Distributed Average Consensus Algorithms in d-Regular Bipartite Graphs: Comparative Study

Kenyeres

2023

Future Internet

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“…In [45], the authors examine the finite-time bipartite consensus problem in multi-agent systems with detail-balanced structure and propose a new weighted signed AC protocol framework.…”

Section: Related Workmentioning

confidence: 99%

“…Primary Focus of Paper Applied Graphs of Our Interest [38] Formulating the necessary and sufficient convergence conditions for MD weights and the generalized Metropolis-Hastings algorithm Bipartite regular [39] Determining the lower bound for the Laplacian eigenvalues Ramanujan non-bipartite [40] A proposal of an algorithm for finite bit-rate communication Ramanujan [41] A proposal of a diffusion-based communication protocol for improving the convergence rate of AC Bipartite regular [5] A proposal of an algorithm for simplifying AC over mobile systems Bipartite regular Bipartite regular components [42] An analysis of consensus algorithms Triangular regular [43] Addressing the observability issue in a consensus network Strongly regular Distance regular [44] An analysis of AC, discovering the Magic Number Regular Irregular [45] An analysis of the finite-time bipartite consensus problem; a proposal of a new weighted signed AC Bipartite [46] An analysis of the bipartite consensus problem in multi-agent systems Bipartite [47] An analysis of the impact of disturbances on bipartite averaging tracking, a proposal of an algorithm to reach the finite-time bipartite averaging tracking Bipartite [48] A proposal of a distributed algorithm for determining a spectral radius…”

Section: Papermentioning

confidence: 99%

Distributed Mechanism for Detecting Average Consensus with Maximum-Degree Weights in Bipartite Regular Graphs

Kenyeres

2021

Mathematics

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In recent decades, distributed consensus-based algorithms for data aggregation have been gaining in importance in wireless sensor networks since their implementation as a complementary mechanism can ensure sensor-measured values with high reliability and optimized energy consumption in spite of imprecise sensor readings. In the presented article, we address the average consensus algorithm over bipartite regular graphs, where the application of the maximum-degree weights causes the divergence of the algorithm. We provide a spectral analysis of the algorithm, propose a distributed mechanism to detect whether a graph is bipartite regular, and identify how to reconfigure the algorithm so that the convergence of the average consensus algorithm is guaranteed over bipartite regular graphs. More specifically, we identify in the article that only the largest and the smallest eigenvalues of the weight matrix are located on the unit circle; the sum of all the inner states is preserved at each iteration despite the algorithm divergence; and the inner states oscillate between two values close to the arithmetic means determined by the initial inner states from each disjoint subset. The proposed mechanism utilizes the first-order forward and backward finite-difference of the inner states (more specifically, five conditions are proposed) to detect whether a graph is bipartite regular or not. Subsequently, the mixing parameter of the algorithm can be reconfigured the way it is identified in this study whereby the convergence of the algorithm is ensured in bipartite regular graphs. In the experimental part, we tested our mechanism over randomly generated bipartite regular graphs, random graphs, and random geometric graphs with various parameters, thereby identifying its very high detection rate and proving that the algorithm can estimate the arithmetic mean with high precision (like in error-free scenarios) after the suggested reconfiguration.

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Signed Average Consensus in Cooperative-Antagonistic Multi-Agent Systems with multiple communication time-varying delays

Caiazzo,

Lui,

Petrillo

et al. 2024

IFAC-PapersOnLine

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A Unified Framework Design for Finite-Time Bipartite Consensus of Multi-Agent Systems

Cited by 5 publications

References 49 publications

Distributed Average Consensus Algorithms in d-Regular Bipartite Graphs: Comparative Study

Distributed Average Consensus Algorithms in d-Regular Bipartite Graphs: Comparative Study

Distributed Mechanism for Detecting Average Consensus with Maximum-Degree Weights in Bipartite Regular Graphs

Signed Average Consensus in Cooperative-Antagonistic Multi-Agent Systems with multiple communication time-varying delays

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