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Accelerated Distributed Primal-Dual Dynamics Using Adaptive Synchronization
P.A. Bansode, K.C. Kosaraju, S.R. Wagh, , N.M. Singh
Published in Institute of Electrical and Electronics Engineers Inc.
2019
Volume: 7
   
Pages: 120424 - 120440
Abstract
This paper proposes an adaptive primal-dual dynamics for distributed optimization in multi-agent systems. The proposed dynamics incorporates an adaptive synchronization law that reinforces the interconnection strength between the coupled agents. By strengthening the synchronization between the primal variables of the coupled agents, the given law accelerates the convergence of the proposed dynamics to the saddle-point solution. The resulting dynamics is represented as a feedback-interconnected networked system that proves to be passive. The passivity properties of the proposed dynamics are exploited along with the LaSalle's invariance principle for hybrid systems, to establish asymptotic convergence and stability of the saddle-point solution. Further, the primal dynamics is analyzed for the rate of convergence and stronger convergence bounds are established, it is proved that the primal dynamics achieve accelerated convergence under the adaptive synchronization. The robustness of the proposed dynamics is quantified using L2-gain analysis and the correlation between the rate of convergence and robustness of the proposed dynamics are presented. The effectiveness of the proposed dynamics is demonstrated by applying it to solve distributed least squares and distributed support vector machines problems. © 2013 IEEE.
About the journal
JournalData powered by TypesetIEEE Access
PublisherData powered by TypesetInstitute of Electrical and Electronics Engineers Inc.
ISSN21693536