Discrete-time dynamic average consensus

Minghui Zhu and Sonia Martínez
Automatica, 46 (2) (2010) 322-329

Abstract:

We propose a class of discrete-time dynamic average consensus algorithms that allow a group of $n$ agents to track the average of their reference inputs. The convergence results rely on the input-to-output stability properties of consensus algorithms and require that the union of communication graphs over a bounded period of time be strongly connected. The only requirement on the set of reference inputs is that the maximum relative difference between the $n^{th}$-order differences of any two reference inputs be bounded for some $n \ge 0$.

File: main.pdf

Bib-tex entry:

@article{MZ-SM:10,
author = {M. Zhu and S. Mart{\'\i}nez},
title = {Discrete-time dynamic average consensus},
journal= {Automatica},
volume ={46},
number ={2},
year = {2010},
pages ={322-329}
}