In this paper we carry out a stability analysis
of a distributed consensus algorithm in presence of
link failures. The algorithm combines a new broadcast
version of a Push-Sum algorithm, specifically designed
for handling link failures, with a new recursive consensus
filter. The analysis is based on the properties of random
Laplacian matrices and random sub-graphs and it may also
be relevant for other distributed estimation problems. We
characterize the convergence speed, the minimum number
of consensus steps needed and the impact of link failures
and for both the broadcast Push-Sum and the recursive
consensus algorithms. Numerical simulations validate the
theoretical analysis.In this paper we carry out a stability analysis
of a distributed consensus algorithm in presence of
link failures. The algorithm combines a new broadcast
version of a Push-Sum algorithm, specifically designed
for handling link failures, with a new recursive consensus
filter. The analysis is based on the properties of random
Laplacian matrices and random sub-graphs and it may also
be relevant for other distributed estimation problems. We
characterize the convergence speed, the minimum number
of consensus steps needed and the impact of link failures
and for both the broadcast Push-Sum and the recursive
consensus algorithms. Numerical simulations validate the
theoretical analysis.
Dettaglio pubblicazione
2023, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, Pages 1-8
Consensus analysis of random sub-graphs for distributed filtering with link failures (01a Articolo in rivista)
Battilotti Stefano, Cacace Filippo, D'Angelo Massimiliano
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