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Chen, Weisheng; Ren, Wei

Event-triggered zero-gradient-sum distributed consensus optimization over directed networks. (English) Zbl 1328.93167

Automatica 65, 90-97 (2016).
Summary: This paper focuses on the event-triggered zero-gradient-sum algorithms for a distributed convex optimization problem over directed networks. The communication process is driven by trigger conditions monitored by nodes. The proposed trigger conditions are decentralized and just depend on each node’s own state. In the continuous-time case, we propose an algorithm based on a sample-based monitoring scheme. In the discrete-time case, we propose a new event-triggered zero-gradient-sum algorithm which is suitable for more general network models. It is proved that two proposed event-triggered algorithms are exponentially convergent if the design parameters are chosen properly and the network topology is strongly connected and weight-balanced. Finally, we illustrate the advantages of the proposed algorithms by numerical simulation.

Cited in 50 Documents

MSC:

93C65 Discrete event control/observation systems
93A14 Decentralized systems
93B40 Computational methods in systems theory (MSC2010)

Keywords:

consensus; event-triggered scheme; distributed optimization; directed network
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References:

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