Distributed Subgradient Method for Constrained Convex Optimization with Quantized and Event-Triggered Communication

Naoki HAYASHI  Kazuyuki ISHIKAWA  Shigemasa TAKAI  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E103-A   No.2   pp.428-434
Publication Date: 2020/02/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.2019MAP0007
Type of Manuscript: Special Section PAPER (Special Section on Mathematical Systems Science and its Applications)
Category: 
Keyword: 
multi-agent systems,  distributed optimization,  quantized communication,  event-triggered control,  

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Summary: 
In this paper, we propose a distributed subgradient-based method over quantized and event-triggered communication networks for constrained convex optimization. In the proposed method, each agent sends the quantized state to the neighbor agents only at its trigger times through the dynamic encoding and decoding scheme. After the quantized and event-triggered information exchanges, each agent locally updates its state by a consensus-based subgradient algorithm. We show a sufficient condition for convergence under summability conditions of a diminishing step-size.