{"title":"复杂网络-物理-人类系统的实时互动决策和控制框架","authors":"Chen-Lian Hu, Lei Wang, Mei-Ling Chen, Cheng Pei","doi":"10.1016/j.arcontrol.2024.100938","DOIUrl":null,"url":null,"abstract":"<div><p>Over the past decade, the advancement of digital technology has significantly enhanced operations management in complex cyber-physical systems (CPSs), especially in the production and manufacturing sectors. In such systems, the physical and cyber spaces are generally connected through sensors, networking, and control actions. With the surge in available real-time data, automation and intelligence have become increasingly prevalent. However, full automation and sophisticated intelligence often remain challenging to achieve in real-world CPSs. Currently, many practical tasks in CPSs are best tackled through the integration of human cognitive skills with autonomous systems, highlighting the indispensable role that humans play in these settings. In this study, we present a framework for real-time decision-making and control in complex cyber-physical-human systems. The framework consists of three main modules: intelligent data processing, intelligent decision-making and control, and human-computer interaction. It is designed to provide a practical and implementable framework for supporting real-time decision-making and control in cyber-physical-human system applications. To demonstrate the applicability of the framework, we build a comprehensive decision support tool to manage several important real-time decision-making and control tasks at a container terminal. The tool is seamlessly integrated into the main operating system of the container terminal and aids decision-makers in making optimal decisions and generating appropriate control actions. The effectiveness of the tool is confirmed by observed improvements in several key operational efficiency indicators at the container terminal.</p></div>","PeriodicalId":50750,"journal":{"name":"Annual Reviews in Control","volume":"57 ","pages":"Article 100938"},"PeriodicalIF":7.3000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A real-time interactive decision-making and control framework for complex cyber-physical-human systems\",\"authors\":\"Chen-Lian Hu, Lei Wang, Mei-Ling Chen, Cheng Pei\",\"doi\":\"10.1016/j.arcontrol.2024.100938\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Over the past decade, the advancement of digital technology has significantly enhanced operations management in complex cyber-physical systems (CPSs), especially in the production and manufacturing sectors. In such systems, the physical and cyber spaces are generally connected through sensors, networking, and control actions. With the surge in available real-time data, automation and intelligence have become increasingly prevalent. However, full automation and sophisticated intelligence often remain challenging to achieve in real-world CPSs. Currently, many practical tasks in CPSs are best tackled through the integration of human cognitive skills with autonomous systems, highlighting the indispensable role that humans play in these settings. In this study, we present a framework for real-time decision-making and control in complex cyber-physical-human systems. The framework consists of three main modules: intelligent data processing, intelligent decision-making and control, and human-computer interaction. It is designed to provide a practical and implementable framework for supporting real-time decision-making and control in cyber-physical-human system applications. To demonstrate the applicability of the framework, we build a comprehensive decision support tool to manage several important real-time decision-making and control tasks at a container terminal. The tool is seamlessly integrated into the main operating system of the container terminal and aids decision-makers in making optimal decisions and generating appropriate control actions. The effectiveness of the tool is confirmed by observed improvements in several key operational efficiency indicators at the container terminal.</p></div>\",\"PeriodicalId\":50750,\"journal\":{\"name\":\"Annual Reviews in Control\",\"volume\":\"57 \",\"pages\":\"Article 100938\"},\"PeriodicalIF\":7.3000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual Reviews in Control\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1367578824000075\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Reviews in Control","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1367578824000075","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
A real-time interactive decision-making and control framework for complex cyber-physical-human systems
Over the past decade, the advancement of digital technology has significantly enhanced operations management in complex cyber-physical systems (CPSs), especially in the production and manufacturing sectors. In such systems, the physical and cyber spaces are generally connected through sensors, networking, and control actions. With the surge in available real-time data, automation and intelligence have become increasingly prevalent. However, full automation and sophisticated intelligence often remain challenging to achieve in real-world CPSs. Currently, many practical tasks in CPSs are best tackled through the integration of human cognitive skills with autonomous systems, highlighting the indispensable role that humans play in these settings. In this study, we present a framework for real-time decision-making and control in complex cyber-physical-human systems. The framework consists of three main modules: intelligent data processing, intelligent decision-making and control, and human-computer interaction. It is designed to provide a practical and implementable framework for supporting real-time decision-making and control in cyber-physical-human system applications. To demonstrate the applicability of the framework, we build a comprehensive decision support tool to manage several important real-time decision-making and control tasks at a container terminal. The tool is seamlessly integrated into the main operating system of the container terminal and aids decision-makers in making optimal decisions and generating appropriate control actions. The effectiveness of the tool is confirmed by observed improvements in several key operational efficiency indicators at the container terminal.
期刊介绍:
The field of Control is changing very fast now with technology-driven “societal grand challenges” and with the deployment of new digital technologies. The aim of Annual Reviews in Control is to provide comprehensive and visionary views of the field of Control, by publishing the following types of review articles:
Survey Article: Review papers on main methodologies or technical advances adding considerable technical value to the state of the art. Note that papers which purely rely on mechanistic searches and lack comprehensive analysis providing a clear contribution to the field will be rejected.
Vision Article: Cutting-edge and emerging topics with visionary perspective on the future of the field or how it will bridge multiple disciplines, and
Tutorial research Article: Fundamental guides for future studies.