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

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 (US)
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 - Sep 30 2008
Event	2008 American Control Conference, ACC - Seattle, WA, United States Duration: Jun 11 2008 → Jun 13 2008

Publication series

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

Other

Other	2008 American Control Conference, ACC
Country/Territory	United States
City	Seattle, WA
Period	6/11/08 → 6/13/08

ASJC Scopus subject areas

Electrical and Electronic Engineering

Online availability

10.1109/ACC.2008.4586605

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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, 6/11/08. https://doi.org/10.1109/ACC.2008.4586605

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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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Multiscale consensus for decentralized estimation and its application to building systems

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