文章基本信息

标题：Cloud-based model predictive control with variable horizon ⁎
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作者：Per Skarin ; Johan Eker ; Karl-Erik Årzén 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：6993-7000
DOI：10.1016/j.ifacol.2020.12.437
语种：English
出版社：Elsevier
摘要：AbstractA novel method using the cloud to implement a variable horizon model predictive controller is presented. In case of sudden long delays and downtime, a graceful degradation is used. Robust, best effort strategies allow industrial grade use of the powerful, efficient, and quickly improving cloud ecosystems. The variable horizon strategy finds use in, for example, non-linear control problems, and the proposed method can be generalized to implement robust and scalable controllers that benefit from cloud technology. We show results from two horizon selection strategies, service degradation and connectivity issues.
关键词：KeywordsIndustry automationPredictive controlOptimal controlSystems conceptSystem architecturesNetworksAdaptive systemsParallelism