系统仿真学报 ›› 2015, Vol. 27 ›› Issue (12): 2927-2934.

• 仿真建模与仿真算法及数值仿真 • 上一篇    下一篇

基于CPN Tools的可重入自动组合设备的建模与仿真

张梅1,2, 陈广森1,2, 游佳1,2   

  1. 1.华南理工大学自动化科学与工程学院,广州 510640;
    2.华南理工大学精密电子制造装备教育部工程研究中心,广州 510640
  • 收稿日期:2014-08-26 修回日期:2015-03-06 出版日期:2015-12-08 发布日期:2020-07-30
  • 作者简介:张梅(1977-), 女, 安徽, 副教授, 硕导, 研究方向为智能优化方法研究、生物医学工程。
  • 基金资助:
    中央高校基本科研业务费专项资金资助(2014zz0033,x2zd-D2153910); 广州市科技重大专项计划—产学研专项资助(2012Y5-00004)

Modeling and Scheduling of Reentrant Automatic Assembly Equipment Based on CPN Tools

Zhang Mei1,2, Chen Guangsen1,2, You Jia1,2   

  1. 1. School of Automation Science and Control Engineering, South China University of Technology, Guangzhou 510640, China;
    2. Engineering Research Centre for Precision Electronic Manufacturing Equipment of Ministry of Education,South China University of Technology, Guangzhou 510640, China
  • Received:2014-08-26 Revised:2015-03-06 Online:2015-12-08 Published:2020-07-30

摘要: 提出将全自动免疫分析检测设备看作一种可重入的双臂自动组合设备。采用时间着色的Petri网(TCPN)对该类检测设备的检测过程进行建模,并利用CPN tools评价模型性能及仿真实验。为优化检测过程,设计了DPC动态投料策略和LSPON、FIFO调度策略,并综合两类策略提出复合控制策略对TCPN模型进行调度求解。针对不同规模的批量检测项目实例在CPN tools平台上结合提出的不同策略进行调度。仿真结果验证了TCPN模型与所提出策略相结合调度方法的合理性。

关键词: 可重入, 自动组合设备, 调度, Petri网, CPN tools

Abstract: The idea about treating automatic immunoassay detection equipment as a reentrant dual-armed automatic assembly equipment was brought forward. Using timed colored Petri nets (TCPN) to model the equipment according to its detection, the performance of model and simulation experiment were evaluated. To optimize the detection process, DPC dynamic feeding strategy and LSPON, FIFO scheduling strategy were designed. Based on that, a hybrid control strategy was proposed to schedule the model more efficiently. Batch-detecting projects of different scale examples were scheduled on the platform of CPN tools according to the strategies above. The simulation results illustrate the reasonability and feasibility of the combination of TCPN model and strategies mentioned previously.

Key words: reentrant automatic, assembly equipment, modeling and scheduling, Petri nets, CPN tool

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