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Distributed Subgradient Method With Edge-Based Event-Triggered Communication
DOI:10.1109/TAC.2018.2800760.png)
摘要
En 中文
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.
Keyword:
Cooperative control
distributed optimization
event-triggered communication
multi-agent systems
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期刊
IF:
7
论文数:
1.3W
被引数:
6.7W
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引用论文
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Quantized subgradient algorithm with limited bandwidth communications for solving distributed optimization over general directed multi-agent networks
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IF6.5

