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Distributed Consensus, Optimization and Computation in Networked Systems

In the first part of this thesis, we propose a distributed consensus algorithm under multi-layer multi-group structure with communication time delays. It is proven that the consensus will be achieved in both time-varying and fixed communication delays. In the second part, we study the distributed optimization problem with a finite-time mechanism. It is shown that our distributed proportional-integral algorithm can exponentially converge to the unique global minimizer when the gain parameters satisfy the sufficient conditions. Moreover, we equip the proposed algorithm with a decentralized algorithm, which enables an arbitrarily chosen agent to compute the exact global minimizer within a finite number of time steps, using its own states observed over a successive time steps. In the third part, it is shown the implementation of accelerated distributed energy management for microgrids is achieved. The results presented in the thesis are corroborated by simulations or experiments.

Identiferoai:union.ndltd.org:unt.edu/info:ark/67531/metadc1404555
Date12 1900
CreatorsYao, Lisha
ContributorsYang, Tao, Fu, Shengli, Li, Xinrong
PublisherUniversity of North Texas
Source SetsUniversity of North Texas
LanguageEnglish
Detected LanguageEnglish
TypeThesis or Dissertation
Formatv, 70 pages, Text
RightsPublic, Yao, Lisha, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved.

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