Multiscale consensus for decentralized estimation and its application to building systems

Jong Han Kim; Matthew West; Eelco Scholte; Satish Narayanan

doi:10.1109/ACC.2008.4586605

Multiscale consensus for decentralized estimation and its application to building systems

Jong Han Kim, Matthew West, Eelco Scholte, Satish Narayanan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

14 Scopus citations

Abstract

Multiscale approaches to accelerate the convergence of decentralized consensus problems are introduced. Consecutive consensus iterations are executed on several scales to achieve fast convergence for networks with poor connectivity. As an example the proposed algorithm is applied to the decentralized Kalman filtering problem for estimation of contaminants in building systems. Two conventional observers are designed and convergence is compared with respect to the number of communications necessary, which is an effective measure of system complexity. It is demonstrated that the proposed multiscale scheme substantially accelerates the decentralized consensus. Future extensions and directions are briefly summarized.

Original language	English
Title of host publication	2008 American Control Conference, ACC
Pages	888-893
Number of pages	6
DOIs	https://doi.org/10.1109/ACC.2008.4586605
State	Published - 2008
Externally published	Yes
Event	2008 American Control Conference, ACC - Seattle, WA, United States Duration: 11 Jun 2008 → 13 Jun 2008

Publication series

Name	Proceedings of the American Control Conference
ISSN (Print)	0743-1619

Conference

Conference	2008 American Control Conference, ACC
Country/Territory	United States
City	Seattle, WA
Period	11/06/08 → 13/06/08

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10.1109/ACC.2008.4586605

Cite this

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title = "Multiscale consensus for decentralized estimation and its application to building systems",

abstract = "Multiscale approaches to accelerate the convergence of decentralized consensus problems are introduced. Consecutive consensus iterations are executed on several scales to achieve fast convergence for networks with poor connectivity. As an example the proposed algorithm is applied to the decentralized Kalman filtering problem for estimation of contaminants in building systems. Two conventional observers are designed and convergence is compared with respect to the number of communications necessary, which is an effective measure of system complexity. It is demonstrated that the proposed multiscale scheme substantially accelerates the decentralized consensus. Future extensions and directions are briefly summarized.",

author = "Kim, {Jong Han} and Matthew West and Eelco Scholte and Satish Narayanan",

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Kim, JH, West, M, Scholte, E & Narayanan, S 2008, Multiscale consensus for decentralized estimation and its application to building systems. in 2008 American Control Conference, ACC., 4586605, Proceedings of the American Control Conference, pp. 888-893, 2008 American Control Conference, ACC, Seattle, WA, United States, 11/06/08. https://doi.org/10.1109/ACC.2008.4586605

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AU - Kim, Jong Han

AU - West, Matthew

AU - Scholte, Eelco

AU - Narayanan, Satish

PY - 2008

Y1 - 2008

N2 - Multiscale approaches to accelerate the convergence of decentralized consensus problems are introduced. Consecutive consensus iterations are executed on several scales to achieve fast convergence for networks with poor connectivity. As an example the proposed algorithm is applied to the decentralized Kalman filtering problem for estimation of contaminants in building systems. Two conventional observers are designed and convergence is compared with respect to the number of communications necessary, which is an effective measure of system complexity. It is demonstrated that the proposed multiscale scheme substantially accelerates the decentralized consensus. Future extensions and directions are briefly summarized.

AB - Multiscale approaches to accelerate the convergence of decentralized consensus problems are introduced. Consecutive consensus iterations are executed on several scales to achieve fast convergence for networks with poor connectivity. As an example the proposed algorithm is applied to the decentralized Kalman filtering problem for estimation of contaminants in building systems. Two conventional observers are designed and convergence is compared with respect to the number of communications necessary, which is an effective measure of system complexity. It is demonstrated that the proposed multiscale scheme substantially accelerates the decentralized consensus. Future extensions and directions are briefly summarized.

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U2 - 10.1109/ACC.2008.4586605

DO - 10.1109/ACC.2008.4586605

M3 - Conference contribution

AN - SCOPUS:52449092209

SN - 9781424420797

T3 - Proceedings of the American Control Conference

SP - 888

EP - 893

BT - 2008 American Control Conference, ACC

T2 - 2008 American Control Conference, ACC

Y2 - 11 June 2008 through 13 June 2008

ER -

Multiscale consensus for decentralized estimation and its application to building systems

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