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...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:IEEE transactions on control of network systems Ročník 5; číslo 1; s. 167 - 178
Hlavní autori: Shuai Liu, Lihua Xie, Quevedo, Daniel E.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: IEEE 01.03.2018
Predmet:
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
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí: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