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Mathematics > Optimization and Control

Title: Distributed Optimization for Second-Order Multi-Agent Systems with Dynamic Event-Triggered Communication

Abstract: In this paper, we propose a fully distributed continuous-time algorithm to solve the distributed optimization problem for second-order multi-agent systems. The optimization objective function is a sum of private cost functions associated to the individual agents and the interaction between agents is described by a weighted undirected graph. We show the exponential convergence of the proposed algorithm if the underlying graph is connected and the private cost functions are strongly convex and have locally Lipschitz gradients. Moreover, to reduce the overall need of communication, we then propose a dynamic event-triggered communication scheme that is free of Zeno behavior. It is shown that the exponential convergence is achieved if the private cost functions are globally Lipschitz. Numerical simulations are provided to illustrate the effectiveness of the theoretical results.
Subjects: Optimization and Control (math.OC)
Cite as: arXiv:1803.06380 [math.OC]
  (or arXiv:1803.06380v1 [math.OC] for this version)

Submission history

From: Xinlei Yi [view email]
[v1] Fri, 16 Mar 2018 19:35:36 GMT (386kb)