Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/159487
Title: Distributed online optimization for multi-agent networks with coupled inequality constraints
Authors: Li, Xiuxian
Yi, Xinlei
Xie, Lihua
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Li, X., Yi, X. & Xie, L. (2020). Distributed online optimization for multi-agent networks with coupled inequality constraints. IEEE Transactions On Automatic Control, 66(8), 3575-3591. https://dx.doi.org/10.1109/TAC.2020.3021011
Project: RG72
Journal: IEEE Transactions on Automatic Control
Abstract: This article investigates the distributed online optimization problem over a multi-agent network subject to local set constraints and coupled inequality constraints, which has a lot of applications in many areas, such as wireless sensor networks, power systems, and plug-in electric vehicles. In this problem, the cost function at each time step is the sum of local cost functions with each of them being gradually revealed to its corresponding agent, and meanwhile only local functions in coupled inequality constraints are accessible to each agent. To address this problem, a modified primal-dual algorithm, called distributed online primal-dual push-sum algorithm, is developed in this article, which does not rest on any assumption on parameter boundedness and is applicable to unbalanced networks. It is shown that the proposed algorithm is sublinear for both the dynamic regret and the violation of coupled inequality constraints. Finally, the theoretical results are supported by a simulation example.
URI: https://hdl.handle.net/10356/159487
ISSN: 0018-9286
DOI: 10.1109/TAC.2020.3021011
Schools: School of Electrical and Electronic Engineering 
Rights: © 2020 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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