文章基本信息

标题：A Hybrid Systems Approach for Distributed Nonsmooth Optimization in Asynchronous Multi-Agent Sampled-Data Systems * * Research supported in part by AFOSR grant number FA9550-15-1-0155, and NSF grant number ECCS-1508757.
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作者：Jorge I. Poveda ; Jorge I. Poveda ; Andrew R. Teel 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：18
页码：152-157
DOI：10.1016/j.ifacol.2016.10.155
语种：English
出版社：Elsevier
摘要：Abstract: We study the problem of robust distributed nonsmooth optimization in a network of sampled data systems with separable response maps but coupled dynamics. Each agent of the network is assumed to have an individual clock and an individual nonsmooth output function, as well as set-valued internal dynamics that are coupled with the internal dynamics of its neighboring agents. In order to achieve robust convergence and stability of the optimal point of the response map of the entire network, we design a distributed deterministic model-free logic-based hybrid controller that globally and robustly synchronizes the clocks of the sampled data systems, while at the same time optimizes the response map of every agent by using only sampled measurements of their individual outputs. We present numerical simulations illustrating the results.
关键词：KeywordsHybrid systemssampled-data systemsmulti-agent systemsadaptive controloptimization