{"title":"Robust Decision-Making for Collaborative Manufacturing in ICPSs via Hierarchical Games","authors":"Xinjiang Cai;Qing Gao;Wei Wang;Jinhu Lü","doi":"10.1109/TICPS.2024.3381083","DOIUrl":null,"url":null,"abstract":"In this article, the robust decision-making problem is investigated for collaborative manufacturing in industrial cyber-physical systems (ICPSs) that involve multiple manufacturing line agents (MLAs) and multiple industrial terminal agents (ITAs). The disturbing factor is modeled as a rational player who aims to optimally deteriorate other players' performance, then the robust decision-making problem is addressed from a game-theoretic perspective by achieving a Nash-Stackelberg-Nash-Saddle (NSNS) equilibrium where all players' information is acquired through a dynamic feedback form. Furthermore, the existence of the NSNS equilibrium is analyzed, and the input-to-state stability of the closed-loop system is proven. Finally, simulations from a numerical example are presented to demonstrate the effectiveness of the proposed approach.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"2 ","pages":"71-80"},"PeriodicalIF":0.0000,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Cyber-Physical Systems","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10478679/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this article, the robust decision-making problem is investigated for collaborative manufacturing in industrial cyber-physical systems (ICPSs) that involve multiple manufacturing line agents (MLAs) and multiple industrial terminal agents (ITAs). The disturbing factor is modeled as a rational player who aims to optimally deteriorate other players' performance, then the robust decision-making problem is addressed from a game-theoretic perspective by achieving a Nash-Stackelberg-Nash-Saddle (NSNS) equilibrium where all players' information is acquired through a dynamic feedback form. Furthermore, the existence of the NSNS equilibrium is analyzed, and the input-to-state stability of the closed-loop system is proven. Finally, simulations from a numerical example are presented to demonstrate the effectiveness of the proposed approach.