Distributed intelligence for plant automation based on multi-agent systems:: the PABADIS approach

被引:42
|
作者
Lüder, A
Peschke, J
Sauter, T
Deter, S
Diep, D
机构
[1] Univ Magdeburg, Inst Arbeitswissensch Fabr Automatisierung & Fab, D-39106 Magdeburg, Germany
[2] Vienna Univ Technol, Inst Comp Technol, A-1040 Vienna, Austria
[3] Univ Marburg, Dept Math & Comp Sci, D-35032 Marburg, Germany
[4] Ecole Mines Ales, Site EERIE, F-30035 Nimes 1, France
关键词
manufacturing; distributed intelligence; control agent technology; mobile code; !text type='JAVA']JAVA[!/text]-based JINI;
D O I
10.1080/09537280410001667484
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
To manage the emerging problems of companies in today's economical surroundings a new thinking in control is required. On the level of field control a step to distributed systems based on distributed intelligence is the state of the art. But on the above levels of control, central and therefore inflexible systems are predominant. This leads to rigid control structures unable to react on system changes with respect to machinery and product programme in a fast and cost-saving way. The PABADIS approach aims in solving the mentioned problems by introduction of horizontal as well as vertical flexibility into the control structure. This flexibility is reached by using mobile and residential agents to establish distributed intelligence on the level of manufacturing execution systems and integration of distributed intelligence on the field control level.
引用
收藏
页码:201 / 212
页数:12
相关论文
共 50 条
  • [31] A Distributed Intelligent Maintenance System based on Artificial Immune Approach and Multi-Agent Systems
    Fasanotti, Luca
    [J]. 2014 12TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN), 2014, : 783 - 786
  • [32] Distributed predictive control of multi-agent systems based on error upper bound approach
    Zhu, Jialin
    Xue, Binqiang
    [J]. IEEE Access, 2021, 9 : 11470 - 11478
  • [33] A multi-agent and distributed ruler based approach to production scheduling of agile manufacturing systems
    Wang, YH
    Yin, CW
    Zhang, Y
    [J]. INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, 2003, 16 (02) : 81 - 92
  • [34] Distributed H∞ consensus of multi-agent systems: a performance region-based approach
    Zhao, Yu
    Duan, Zhisheng
    Wen, Guanghui
    Chen, Guanrong
    [J]. INTERNATIONAL JOURNAL OF CONTROL, 2012, 85 (03) : 332 - 341
  • [35] Distributed Predictive Control of Multi-Agent Systems Based on Error Upper Bound Approach
    Zhu, Jialin
    Xue, Binqiang
    [J]. IEEE ACCESS, 2021, 9 : 11470 - 11478
  • [36] Coordinated Localization and Circumnavigation of Multi-Agent Systems: A Distributed Observer-Based Approach
    Wang, Lei
    Zou, Yao
    Meng, Ziyang
    [J]. 2019 IEEE 15TH INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION (ICCA), 2019, : 1540 - 1544
  • [37] Research on a distributed artificial intelligence and multi-agent system
    Yin, Huayi
    Liu, Lizhao
    Zhong, Ying
    [J]. AGRO FOOD INDUSTRY HI-TECH, 2017, 28 (01): : 2122 - 2126
  • [38] Distributed Multi-Agent Coordination: A Comparison Lemma Based Approach
    Cao, Yongcan
    Ren, Wei
    [J]. 2011 AMERICAN CONTROL CONFERENCE, 2011,
  • [39] Multi-agent system: An introduction to distributed artificial intelligence
    Rouchier, J
    [J]. JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION, 2001, 4 (02): : U213 - U219
  • [40] Approach to the Distributed Job Shop Scheduling Based on Multi-agent
    Zhang Yu-xian
    Li Lei
    Wang Hong
    Zhao Yan-yan
    Guo Xu
    Meng Chun-hua
    [J]. 2008 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6, 2008, : 2031 - 2034