Fast Distributed Method of Multiplier for Coupled Lagrangian Problems: A Control Approach

Abhishek Rawat, Nicola Elia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this paper, we propose a method for solving the distributed optimization problem in which the objective function is the sum of separable convex functions with linear constraints. We modify the distributed Method of Multiplier algorithm based on [16] by looking it as a potential Proportional Integral (PI) controller. This enables us to obtain the algorithm in which the convergence speed is greatly improved due to different proportionality constants of PI compensator. The relation between these proportionality constants is determined by the positive real property of the algorithm when viewed as a dynamical system.

Original languageEnglish (US)
Title of host publication2018 IEEE Conference on Decision and Control, CDC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5445-5450
Number of pages6
ISBN (Electronic)9781538613955
DOIs
StatePublished - Jul 2 2018
Event57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States
Duration: Dec 17 2018Dec 19 2018

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2018-December
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference57th IEEE Conference on Decision and Control, CDC 2018
Country/TerritoryUnited States
CityMiami
Period12/17/1812/19/18

Bibliographical note

Funding Information:
This work was supported by NSF grants CNS-1239319 and CCF- 1320643, and AFOSR grant FA 9550-15-1-0119. This work was performed when the authors were with the Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.

Funding Information:
*This work was supported by NSF grants CNS-1239319 and CCF-1320643, and AFOSR grant FA 9550-15-1-0119. This work was performed when the authors were with the Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.

Publisher Copyright:
© 2018 IEEE.

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