Eulerian consensus networks

Daniel Zelazo; Frank Allgower

doi:10.1109/CDC.2012.6425921

Eulerian consensus networks

Research output: Contribution to journal › Conference article › peer-review

Abstract

This work considers a special class of consensus seeking networks that we term Eulerian consensus networks. These consensus networks are defined over the class of graphs known as Eulerian, and admit many combinatorial features that are beneficial for both analysis and synthesis purposes. We first consider the H₂ performance of Eulerian consensus systems and reveal that the performance is related to the length of cycles in the graph. The structure of Eulerian graphs motivates a procedure for designing large-scale Eulerian consensus networks. We propose a suite of algorithms for constructing these networks and demonstrate their numerical effectiveness on a graph with 5000 nodes.

Original language	English
Article number	6425921
Pages (from-to)	4715-4720
Number of pages	6
Journal	Proceedings of the IEEE Conference on Decision and Control
DOIs	https://doi.org/10.1109/CDC.2012.6425921
State	Published - 2012
Externally published	Yes
Event	51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States Duration: 10 Dec 2012 → 13 Dec 2012

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Modelling and Simulation
Control and Optimization

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10.1109/CDC.2012.6425921

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title = "Eulerian consensus networks",

abstract = "This work considers a special class of consensus seeking networks that we term Eulerian consensus networks. These consensus networks are defined over the class of graphs known as Eulerian, and admit many combinatorial features that are beneficial for both analysis and synthesis purposes. We first consider the H2 performance of Eulerian consensus systems and reveal that the performance is related to the length of cycles in the graph. The structure of Eulerian graphs motivates a procedure for designing large-scale Eulerian consensus networks. We propose a suite of algorithms for constructing these networks and demonstrate their numerical effectiveness on a graph with 5000 nodes.",

author = "Daniel Zelazo and Frank Allgower",

year = "2012",

doi = "10.1109/CDC.2012.6425921",

language = "الإنجليزيّة",

pages = "4715--4720",

journal = "Proceedings of the IEEE Conference on Decision and Control",

issn = "0743-1546",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "51st IEEE Conference on Decision and Control, CDC 2012 ; Conference date: 10-12-2012 Through 13-12-2012",

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AU - Zelazo, Daniel

AU - Allgower, Frank

PY - 2012

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AB - This work considers a special class of consensus seeking networks that we term Eulerian consensus networks. These consensus networks are defined over the class of graphs known as Eulerian, and admit many combinatorial features that are beneficial for both analysis and synthesis purposes. We first consider the H2 performance of Eulerian consensus systems and reveal that the performance is related to the length of cycles in the graph. The structure of Eulerian graphs motivates a procedure for designing large-scale Eulerian consensus networks. We propose a suite of algorithms for constructing these networks and demonstrate their numerical effectiveness on a graph with 5000 nodes.

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U2 - 10.1109/CDC.2012.6425921

DO - 10.1109/CDC.2012.6425921

M3 - مقالة من مؤنمر

SN - 0743-1546

SP - 4715

EP - 4720

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

M1 - 6425921

T2 - 51st IEEE Conference on Decision and Control, CDC 2012

Y2 - 10 December 2012 through 13 December 2012

ER -

Eulerian consensus networks

Abstract

All Science Journal Classification (ASJC) codes

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