Singularly perturbed filters for dynamic average consensus

Solmaz S. Kia, Jorge Cortés, and Sonia Martínez
Proceedings of the 2013 European Control Conference, Zürich, Switzerland, July 2013

Abstract:

This paper proposes two continuous-time dynamic average consensus algorithms for networks with strongly connected and weight-balanced interaction topologies. The proposed algorithms, termed "$1$st-Order-Input Dynamic Consensus" and "$2$nd-Order-Input Dynamic Consensus", respectively, allow agents to track the average of their dynamic inputs within an $O(\epsilon)$-neighborhood with a pre-specified rate. The only requirement on the set of reference inputs is having continuous bounded derivatives, up to second order for \algorithmoneAbb and up to third order for \algorithmtwoAbb. The correctness analysis of the algorithms relies on singular perturbation theory for non-autonomous dynamical systems. When dynamic inputs are offset from one another by static values, we show that \algorithmtwoAbb converges to the exact dynamic average with no steady-state error. Simulations illustrate our results.

File: main.pdf

Bib-tex entry:

@InProceedings{SSK-JC-SM:13-ecc},
author = {S. S. Kia and J. Cort\'es and S. Mart{\'\i}nez},
booktitle = {Proc. of the 2013 European Control Conference},
title = {Singularly perturbed filters for dynamic average consensus},
year = {2013},
address ={Zürich, Switzerland}
}