A decomposition approach to distributed analysis of networked systems

Cédric Langbort; Lin Xiao; Raffaello D'Andrea; Stephen Boyd

doi:10.1109/cdc.2004.1429372

A decomposition approach to distributed analysis of networked systems

Cédric Langbort, Lin Xiao, Raffaello D'Andrea, Stephen Boyd

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

Abstract

We present a simple distributed algorithm for analyzing well-posedness and stability of a system composed of different sub-units, interconnected over an arbitrary graph. The procedure consists in solving a set of coupled linear matrix inequalities via a subgradient method, with primal decomposition. The proposed algorithm can be implemented in parallel on the system's graph and should prove more efficient than conventional semidefinite programming solvers, for very large systems with a high number of states and interconnection variables.

Original language	English (US)
Article number	ThC10.1
Pages (from-to)	3980-3985
Number of pages	6
Journal	Proceedings of the IEEE Conference on Decision and Control
Volume	4
DOIs	https://doi.org/10.1109/cdc.2004.1429372
State	Published - 2004
Externally published	Yes
Event	2004 43rd IEEE Conference on Decision and Control (CDC) - Nassau, Bahamas Duration: Dec 14 2004 → Dec 17 2004

ASJC Scopus subject areas

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

Online availability

10.1109/cdc.2004.1429372

Library availability

Discover UIUC Full Text

Cite this

@article{66a90e33691a4bdead6c845708e249a7,

title = "A decomposition approach to distributed analysis of networked systems",

abstract = "We present a simple distributed algorithm for analyzing well-posedness and stability of a system composed of different sub-units, interconnected over an arbitrary graph. The procedure consists in solving a set of coupled linear matrix inequalities via a subgradient method, with primal decomposition. The proposed algorithm can be implemented in parallel on the system's graph and should prove more efficient than conventional semidefinite programming solvers, for very large systems with a high number of states and interconnection variables.",

author = "C{\'e}dric Langbort and Lin Xiao and Raffaello D'Andrea and Stephen Boyd",

year = "2004",

doi = "10.1109/cdc.2004.1429372",

language = "English (US)",

volume = "4",

pages = "3980--3985",

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

issn = "0743-1546",

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

note = "2004 43rd IEEE Conference on Decision and Control (CDC) ; Conference date: 14-12-2004 Through 17-12-2004",

}

TY - JOUR

T1 - A decomposition approach to distributed analysis of networked systems

AU - Langbort, Cédric

AU - Xiao, Lin

AU - D'Andrea, Raffaello

AU - Boyd, Stephen

PY - 2004

Y1 - 2004

N2 - We present a simple distributed algorithm for analyzing well-posedness and stability of a system composed of different sub-units, interconnected over an arbitrary graph. The procedure consists in solving a set of coupled linear matrix inequalities via a subgradient method, with primal decomposition. The proposed algorithm can be implemented in parallel on the system's graph and should prove more efficient than conventional semidefinite programming solvers, for very large systems with a high number of states and interconnection variables.

AB - We present a simple distributed algorithm for analyzing well-posedness and stability of a system composed of different sub-units, interconnected over an arbitrary graph. The procedure consists in solving a set of coupled linear matrix inequalities via a subgradient method, with primal decomposition. The proposed algorithm can be implemented in parallel on the system's graph and should prove more efficient than conventional semidefinite programming solvers, for very large systems with a high number of states and interconnection variables.

UR - http://www.scopus.com/inward/record.url?scp=14244262214&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=14244262214&partnerID=8YFLogxK

U2 - 10.1109/cdc.2004.1429372

DO - 10.1109/cdc.2004.1429372

M3 - Conference article

AN - SCOPUS:14244262214

SN - 0743-1546

VL - 4

SP - 3980

EP - 3985

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

M1 - ThC10.1

T2 - 2004 43rd IEEE Conference on Decision and Control (CDC)

Y2 - 14 December 2004 through 17 December 2004

ER -

A decomposition approach to distributed analysis of networked systems

Abstract

ASJC Scopus subject areas

Online availability

Library availability

Related links

Fingerprint

Cite this