Distributed Subgradient Method With Edge-Based Event-Triggered Communication

This paper proposes a distributed subgradient method for constrained optimization with event-triggered communications. In the proposed method, each agent has an estimate of an optimal solution as a state and iteratively updates it by a consensus-based subgradient algorithm with a projection to a com...

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Bibliographic Details
Published in:IEEE transactions on automatic control Vol. 63; no. 7; pp. 2248 - 2255
Main Authors: Kajiyama, Yuichi, Hayashi, Naoki, Takai, Shigemasa
Format: Journal Article
Language:English
Published: IEEE 01.07.2018
Subjects:
Algorithm design and analysis
Convergence
Convex functions
Cooperative control
distributed optimization
event-triggered communication
Linear programming
Multi-agent systems
Optimization
Simulation
ISSN:0018-9286, 1558-2523
Online Access:Get full text
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Summary:This paper proposes a distributed subgradient method for constrained optimization with event-triggered communications. In the proposed method, each agent has an estimate of an optimal solution as a state and iteratively updates it by a consensus-based subgradient algorithm with a projection to a common constraint set. The local communications are carried out by the edge-based triggering mechanism when the difference between the current state and the last triggered state exceeds a threshold. We show that the states of all agents asymptotically converge to one of the optimal solutions under a diminishing and summability condition on a stepsize and a threshold for a trigger condition. We also investigate the convergence rate with respect to the time-averaged state of each agent. The simulation results show that the proposed event-triggered algorithm can reduce the number of communications compared to the time-triggered algorithms.
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2018.2800760