Event-Triggered Quantized Communication-Based Distributed Convex Optimization

A NOVEL distributed algorithm based on multiple agents with continuous-time dynamics is proposed for a convex optimization problem where the objective function is the summation of local objective functions and the state of each agent is subject to a convex constraint set. Considering the limited ban...

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Bibliographic Details
Published in:IEEE transactions on control of network systems Vol. 5; no. 1; pp. 167 - 178
Main Authors: Shuai Liu, Lihua Xie, Quevedo, Daniel E.
Format: Journal Article
Language:English
Published: IEEE 01.03.2018
Subjects:
Algorithm design and analysis
Broadcasting
Communication networks
Convex functions
Distributed algorithms
distributed algorithms/control
event trigger
Heuristic algorithms
Optimization
quantization
Quantization (signal)
ISSN:2325-5870, 2372-2533
Online Access:Get full text
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Summary:A NOVEL distributed algorithm based on multiple agents with continuous-time dynamics is proposed for a convex optimization problem where the objective function is the summation of local objective functions and the state of each agent is subject to a convex constraint set. Considering the limited bandwidth of the communication channels, we introduce a dynamic quantizer for each agent. To further save on communication costs, we develop an event-based broadcasting scheme for each agent. In comparison with algorithms that rely on continuous communication, the proposed algorithm serves to save communication expenditure by exploiting temporal and spatial aspects. Though a joint design of dynamic quantizers and event-trigger functions are under mild conditions, the states of the agents asymptotically approach the global optimal point with an adjustable error bound without incurring Zeno behavior.
ISSN:2325-5870
2372-2533
DOI:10.1109/TCNS.2016.2585305