Title
Robust discrete time dynamic average consensus.
Abstract
This paper deals with the problem of average consensus of a set of time-varying reference signals in a distributed manner. We propose a new class of discrete time algorithms that are able to track the average of the signals with an arbitrarily small steady-state error and with robustness to initialization errors. We provide bounds on the maximum step size allowed to ensure convergence to the consensus with error below the desired one. In addition, for certain classes of reference inputs, the proposed algorithms allow arbitrarily large step size, an important issue in real networks, where there are constraints in the communication rate between the nodes. The robustness to initialization errors is achieved by introducing a time-varying sequence of damping factors that mitigates past errors. Convergence properties are shown by the decomposition of the algorithms into sequences of static consensus processes. Finally, simulation results corroborate the theoretical contributions of the paper.
Year
DOI
Venue
2014
10.1016/j.automatica.2014.10.005
Automatica
Keywords
Field
DocType
Dynamic average consensus,Multi-agent systems,Robust distributed algorithms
Convergence (routing),Mathematical optimization,Average consensus,Control theory,Computer science,Multi-agent system,Robustness (computer science),Discrete time and continuous time,Initialization,Arbitrarily large
Journal
Volume
Issue
ISSN
50
12
0005-1098
Citations 
PageRank 
References 
7
0.45
11
Authors
4
Name
Order
Citations
PageRank
Eduardo Montijano121422.27
Juan Ignacio Montijano2191.14
Carlos Sagüés344339.22
Sonia Mart ´ inez485658.27