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复杂工业过程智能优化决策系统的现状与展望

丁进良 杨翠娥 陈远东 柴天佑

丁进良, 杨翠娥, 陈远东, 柴天佑. 复杂工业过程智能优化决策系统的现状与展望. 自动化学报, 2018, 44(11): 1931-1943. doi: 10.16383/j.aas.2018.c180550
引用本文: 丁进良, 杨翠娥, 陈远东, 柴天佑. 复杂工业过程智能优化决策系统的现状与展望. 自动化学报, 2018, 44(11): 1931-1943. doi: 10.16383/j.aas.2018.c180550
DING Jin-Liang, YANG Cui-E, CHEN Yuan-Dong, CHAI Tian-You. Research Progress and Prospects of Intelligent Optimization Decision Making in Complex Industrial Process. ACTA AUTOMATICA SINICA, 2018, 44(11): 1931-1943. doi: 10.16383/j.aas.2018.c180550
Citation: DING Jin-Liang, YANG Cui-E, CHEN Yuan-Dong, CHAI Tian-You. Research Progress and Prospects of Intelligent Optimization Decision Making in Complex Industrial Process. ACTA AUTOMATICA SINICA, 2018, 44(11): 1931-1943. doi: 10.16383/j.aas.2018.c180550

复杂工业过程智能优化决策系统的现状与展望

doi: 10.16383/j.aas.2018.c180550
基金项目: 

国家工信部智能制造专项项目 20171122-6

国家自然科学基金 61525302

国家自然科学基金 61590922

沈阳市双百工程项目 Y17-0-004

详细信息
    作者简介:

    杨翠娥  东北大学流程工业综合自动化国家重点实验室博士研究生.2016年获得东北大学信息科学与工程学院硕士学位.主要研究方向为计算智能及其应用.E-mail:cuieyang@outlook.com

    陈远东  东北大学流程工业自动化国家重点实验室博士研究生.主要研究方向为炼厂调度, 混合整数线性规划, 大规模优化算法.E-mail:cyd4999@126.com

    柴天佑  中国工程院院士, 东北大学教授, IEEEFellow, IFAC Fellow.1985年获得东北大学博士学位.主要研究方向为自适应控制, 智能解耦控制, 流程工业综台自动化理论、方法与技术.E-mail:tychai@mail.neu.edu.cn

    通讯作者:

    丁进良东北大学流程工业综合自动化国家重点实验室教授.主要研究方向为复杂工业过程的建模与运行优化控制, 计算智能及应用.本文通信作者.E-mail:jlding@mail.neu.edu.cn

Research Progress and Prospects of Intelligent Optimization Decision Making in Complex Industrial Process

Funds: 

the Project of Ministry of Industry and Information Technology of China 20171122-6

National Natural Science Foundation of China 61525302

National Natural Science Foundation of China 61590922

the Projects of Shenyang Y17-0-004

More Information
    Author Bio:

     Ph.D. candidate at the State Key Laboratory of Synthetical Automation for Process Industies, Northeastern University. She received her master degree from the College of Informdtion Science and Engineering, Northeastern University in 2016. Her research interest covers computational intelligence and its application

     Ph. D. candidate at the State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University. His research interest covers refinery scheduling, mixed integer linear programming, and large-scale optimization algorithm

      Academician of Chinese Academy of Engineering, professor at Northeastern University, IEEE Fellow, IFAC Fellow. He received his Ph. D. degree from Northeastern University in 1985. His research interest covers adaptive control, intelligent decoupling control, and integrated automation theory, method and technology of industrial process

    Corresponding author: DING Jin-Liang  Professor at the State Key Laboratory of Synthetical Automation for Process Industies, Northeastern University. His research interest covers modeling and operation optimization control of complex industrial process, computational intelligence and its application. Corresponding author of this paper
  • 摘要: 流程工业是制造业的重要组成部分,是我国国民经济和社会发展的重要支柱产业.新一代信息技术和人工智能技术为流程工业的发展带来新的挑战和机遇.只有与流程工业的特点与目标密切结合,充分利用大数据,将人工智能、移动互联网、云计算、建模、控制与优化等信息技术与工业生产过程的物理资源紧密融合与协同,实现流程工业智能优化制造,才可能实现流程工业的跨越式发展.本文聚焦流程工业的复杂生产过程,从其智能优化决策系统的角度,描述了复杂工业过程优化决策系统的问题、回顾总结了复杂工业过程全流程优化决策系统的现状,分析了智能优化决策系统的必要性,提出了智能优化决策系统的发展目标及愿景,并对智能优化决策系统的下一步重点研究方向进行了展望.
    1)  本文责任编委 孙健
  • 图  1  复杂工业过程智能优化决策系统的结构示意图

    Fig.  1  Diagram of intelligent optimization decision making system for complex industrial process

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  • 收稿日期:  2018-08-16
  • 录用日期:  2018-10-08
  • 刊出日期:  2018-11-20

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