Dynamic Max-Consensus and Size Estimation of Anonymous Multi-Agent Networks

Fuente: arXiv
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Autores principales: Deplano, Diego, Franceschelli, Mauro, Giua, Alessandro
Formato: Preprint
Publicado: 2020
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author Deplano, Diego
Franceschelli, Mauro
Giua, Alessandro
author_facet Deplano, Diego
Franceschelli, Mauro
Giua, Alessandro
contents In this paper we propose a novel consensus protocol for discrete-time multi-agent systems (MAS), which solves the dynamic consensus problem on the max value, i.e., the dynamic max-consensus problem. In the dynamic max-consensus problem to each agent is fed a an exogenous reference signal, the objective of each agent is to estimate the instantaneous and time-varying value of the maximum among the signals fed to the network, by exploiting only local and anonymous interactions among the agents. The absolute and relative tracking error of the proposed distributed control protocol is theoretically characterized and is shown to be bounded and by tuning its parameters it is possible to trade-off convergence time for steady-state error. The dynamic Max-consensus algorithm is then applied to solve the distributed size estimation problem in a dynamic setting where the size of the network is time-varying during the execution of the estimation algorithm. Numerical simulations are provided to corroborate the theoretical analysis.
format Preprint
id arxiv_https___arxiv_org_abs_2009_03858
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Dynamic Max-Consensus and Size Estimation of Anonymous Multi-Agent Networks
Deplano, Diego
Franceschelli, Mauro
Giua, Alessandro
Optimization and Control
Systems and Control
In this paper we propose a novel consensus protocol for discrete-time multi-agent systems (MAS), which solves the dynamic consensus problem on the max value, i.e., the dynamic max-consensus problem. In the dynamic max-consensus problem to each agent is fed a an exogenous reference signal, the objective of each agent is to estimate the instantaneous and time-varying value of the maximum among the signals fed to the network, by exploiting only local and anonymous interactions among the agents. The absolute and relative tracking error of the proposed distributed control protocol is theoretically characterized and is shown to be bounded and by tuning its parameters it is possible to trade-off convergence time for steady-state error. The dynamic Max-consensus algorithm is then applied to solve the distributed size estimation problem in a dynamic setting where the size of the network is time-varying during the execution of the estimation algorithm. Numerical simulations are provided to corroborate the theoretical analysis.
title Dynamic Max-Consensus and Size Estimation of Anonymous Multi-Agent Networks
topic Optimization and Control
Systems and Control
url https://arxiv.org/abs/2009.03858