Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/143537
Title: Exact convergence of gradient-free distributed optimization method in a multi-agent system
Authors: Pang, Yipeng
Hu, Guoqiang
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2019
Source: Pang, Y., & Hu, G. (2018). Exact convergence of gradient-free distributed optimization method in a multi-agent system. 2018 IEEE Conference on Decision and Control (CDC), 5728-5733. doi:10.1109/CDC.2018.8619028
Abstract: © 2018 IEEE. In this paper, a gradient-free algorithm is proposed for a set constrained distributed optimization problem in a multi-agent system under a directed communication network. For each agent, a pseudo-gradient is designed locally and utilized instead of the true gradient information to guide the decision variables update. Compared with most gradient-free optimization methods where a doubly-stochastic weighting matrix is usually employed, this algorithm uses a row-stochastic matrix plus a column-stochastic matrix, and is able to achieve exact asymptotic convergence to the optimal solution.
URI: https://hdl.handle.net/10356/143537
ISBN: 9781538613955
DOI: 10.1109/CDC.2018.8619028
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, in any current or future media, including reprinting/republishing this material for adverstising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at:https://doi.org/10.1109/CDC.2018.8619028
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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