An Intelligent Control System of Candy Production Process

被引：0
|
作者：
Zhang, Jialiang [1 ]
Li, Beizhi [1 ]
Yang, Jianguo [1 ]
Chen, Hanyan [2 ]
机构：
[1] Donghua Univ, Coll Mech Engn, Shanghai, Peoples R China
[2] Guan Sheng Yuan Grp Co Ltd, Shanghai, Peoples R China
来源：
ADVANCED RESEARCH ON MATERIAL ENGINEERING, CHEMISTRY AND BIOINFORMATICS, PTS 1 AND 2 (MECB 2011) | 2011年 / 282-283卷
关键词：
Intelligent control; Virtual instrument; Data fusion; Candy production; INSTRUMENTATION; SENSORS;
D O I：
10.4028/www.scientific.net/AMR.282-283.658
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Candy production processes involve many process variables. Operators often find it difficult to effectively monitor the process data, analyze current states, detect and diagnose process anomalies, and take appropriate actions to control the processes. The objective of this work is to develop an intelligent control system of candy production process to improve final candy quality and to increase production efficiency with good human-machine interfaces. The study is conducted by using virtual instrument, multi-sensor data fusion and fuzzy control technology to online detect and control typical parameters. Experiment results show that this system can reach requirements of processing accuracy and real-time property and is highly cost-efficient and practical.
引用
收藏
页码：658 / +
页数：2
相关论文
共 50 条
  • [31] Intelligent Hand Posture Recognition System Integrated to Process Control
    Coelho, Y. L.
    Salomao, J. M.
    Kulitz, H. R.
    [J]. IEEE LATIN AMERICA TRANSACTIONS, 2017, 15 (06) : 1144 - 1153
  • [32] AN INTELLIGENT SUPERVISORY SYSTEM FOR ONLINE STATISTICAL PROCESS-CONTROL
    KAYA, A
    [J]. PROCEEDINGS OF THE 28TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-3, 1989, : 781 - 782
  • [33] An Intelligent Automated Control System of Micro Arc Oxidation Process
    Golubkov, P.
    Pecherskaya, E.
    Zinchenko, T.
    [J]. ADVANCES IN AUTOMATION, 2020, 641 : 1053 - 1061
  • [34] Hybrid Intelligent Inverse Optimal Control for Methane Production in an Anaerobic Process
    Gurubel, K. J.
    Ornelas-Tellez, F.
    Sanchez, E. N.
    Carlos-Hernandez, S.
    [J]. CHEMICAL AND BIOCHEMICAL ENGINEERING QUARTERLY, 2013, 27 (02) : 197 - 210
  • [35] An intelligent system for distributed control of an anaerobic wastewater treatment process
    Flores, J
    Arcay, B
    Arias, J
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2000, 13 (04) : 485 - 494
  • [36] Expert PID intelligent process control system with learning functions
    Yang, Weimin
    Wu, Qibing
    [J]. DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES A-MATHEMATICAL ANALYSIS, 2006, 13 : 780 - 784
  • [37] Intelligent Monitoring and Decision Control System for Peripheral Milling Process
    Vallejo, Antonio J.
    Morales-Menendez, Ruben
    Alique, J. R.
    [J]. 2008 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC), VOLS 1-6, 2008, : 1619 - +
  • [38] Hierarchical Intelligent Control System and Its Application to the Sintering Process
    Wang, Chun-Sheng
    Wu, Min
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2013, 9 (01) : 190 - 197
  • [39] Intelligent Methods for Process Control and Diagnostics of a Mill Fan System
    Doukovska, Lyubka A.
    Vassileva, Svetla I.
    [J]. CYBERNETICS AND INFORMATION TECHNOLOGIES, 2014, 14 (01) : 151 - 160
  • [40] Hybrid intelligent system for supervisory control of mineral grinding process
    Ding, Jinliang
    Zhou, Ping
    Liu, Changxin
    Chai, Tianyou
    [J]. ISDA 2006: SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, VOL 1, 2006, : 979 - 984
12345