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  • 标题:Priced Timed Automata Models for Control of Intelligent Product Agents in Manufacturing Systems ⁎
  • 本地全文:下载
  • 作者:Ilya Kovalenko ; Dawn Tilbury ; Kira Barton
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:4
  • 页码:136-142
  • DOI:10.1016/j.ifacol.2021.04.051
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractTo enable product customization and incorporate customer requirements during production, there is a need to integrate more flexible control strategies into the shop floor. One type of strategy that has been proposed to address these challenges is multi-agent control. An integral part of this control strategy is the product agent, a controller for an individual part in the manufacturing system. The product agent uses a continuously updated model of the local manufacturing system to make decisions. However, current models used by product agents do not explicitly incorporate the system’s time constraints. This work proposes a priced timed automata modeling framework to represent an environment model for a product agent. The proposed environment model incorporates personalized production requirements and system constraints for the product agent. To make decisions, the product agent solves an optimization problem with the environment model. A semiconductor manufacturing simulation showcases how multiple product agents can use this model to drive the production of customized parts.
  • 关键词:KeywordsMulti-agent controlintelligent manufacturing systemspriced timed automata
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