Scalability and Fragility in Bounded-Degree Consensus Networks
(2019) 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems, NECSYS 2019 In IFAC-PapersOnLine 52. p.85-90- Abstract
We investigate the performance of linear consensus algorithms subject to a scaling of the underlying network size. Specifically, we model networked systems with nth order integrator dynamics over families of undirected, weighted graphs with bounded nodal degrees. In such networks, the algebraic connectivity affects convergence rates, sensitivity, and, for high-order consensus [n ≥ 3), stability properties. This connectivity scales unfavorably in network size, except in expander families, where consensus performs well regardless of network size. We show, however, that consensus over expander families is fragile to a grounding of the network (resulting in leader-follower consensus). We show that grounding may deteriorate system... (More)
We investigate the performance of linear consensus algorithms subject to a scaling of the underlying network size. Specifically, we model networked systems with nth order integrator dynamics over families of undirected, weighted graphs with bounded nodal degrees. In such networks, the algebraic connectivity affects convergence rates, sensitivity, and, for high-order consensus [n ≥ 3), stability properties. This connectivity scales unfavorably in network size, except in expander families, where consensus performs well regardless of network size. We show, however, that consensus over expander families is fragile to a grounding of the network (resulting in leader-follower consensus). We show that grounding may deteriorate system performance by orders of magnitude in large networks, or cause instability in high-order consensus. Our results, which we illustrate through simulations, also point to a fundamental limitation to the scalability of consensus networks with leaders, which does not apply to leaderless networks.
(Less)
- author
- Tegling, Emma LU ; Middleton, Richard H. and Seron, Maria M.
- publishing date
- 2019
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Distributed control, Large-scale systems, Robustness
- host publication
- 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems
- series title
- IFAC-PapersOnLine
- volume
- 52
- edition
- 20
- pages
- 6 pages
- conference name
- 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems, NECSYS 2019
- conference location
- Chicago, United States
- conference dates
- 2019-09-16 - 2019-09-17
- external identifiers
-
- scopus:85082692930
- ISSN
- 2405-8963
- DOI
- 10.1016/j.ifacol.2019.12.131
- project
- Fundamental mechanisms for scalable control of large networks
- language
- English
- LU publication?
- no
- additional info
- Publisher Copyright: © 2019 IFAC-PapersOnLine. All rights reseved.
- id
- 1266b0f3-987a-48ed-a921-7779e3ac6915
- date added to LUP
- 2021-11-24 09:49:04
- date last changed
- 2023-01-24 21:11:42
@inproceedings{1266b0f3-987a-48ed-a921-7779e3ac6915,
abstract = {{<p>We investigate the performance of linear consensus algorithms subject to a scaling of the underlying network size. Specifically, we model networked systems with n<sup>th</sup> order integrator dynamics over families of undirected, weighted graphs with bounded nodal degrees. In such networks, the algebraic connectivity affects convergence rates, sensitivity, and, for high-order consensus [n ≥ 3), stability properties. This connectivity scales unfavorably in network size, except in expander families, where consensus performs well regardless of network size. We show, however, that consensus over expander families is fragile to a grounding of the network (resulting in leader-follower consensus). We show that grounding may deteriorate system performance by orders of magnitude in large networks, or cause instability in high-order consensus. Our results, which we illustrate through simulations, also point to a fundamental limitation to the scalability of consensus networks with leaders, which does not apply to leaderless networks.</p>}},
author = {{Tegling, Emma and Middleton, Richard H. and Seron, Maria M.}},
booktitle = {{8th IFAC Workshop on Distributed Estimation and Control in Networked Systems}},
issn = {{2405-8963}},
keywords = {{Distributed control; Large-scale systems; Robustness}},
language = {{eng}},
pages = {{85--90}},
series = {{IFAC-PapersOnLine}},
title = {{Scalability and Fragility in Bounded-Degree Consensus Networks}},
url = {{http://dx.doi.org/10.1016/j.ifacol.2019.12.131}},
doi = {{10.1016/j.ifacol.2019.12.131}},
volume = {{52}},
year = {{2019}},
}