计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (30): 241-244.DOI: 10.3778/j.issn.1002-8331.2010.30.068

• 工程与应用 • 上一篇    下一篇

真空冷冻干燥温度的智能预测控制

李晓斌1,2,王海波2   

  1. 1.上海应用技术学院,上海 200235
    2.兰州理工大学 电气与信息工程学院,兰州 730050
  • 收稿日期:2009-12-16 修回日期:2010-01-25 出版日期:2010-10-21 发布日期:2010-10-21
  • 通讯作者: 李晓斌

Intelligent predicting control of vacuum freeze-drying temperature

LI Xiao-bin1,2,WANG Hai-bo2   

  1. 1.Shanghai Institute of Technology,Shanghai 200235,China
    2.College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China
  • Received:2009-12-16 Revised:2010-01-25 Online:2010-10-21 Published:2010-10-21
  • Contact: LI Xiao-bin

摘要: 真空冷冻干燥过程中,升华温度的精确控制是一个大时滞、非线性的控制问题,实际测试表明,现有的PID控制很难实现对升华温度的精确动态跟踪控制,影响冻干物质的物理、化学和生物性状,尤其是生物制品的活性等。提出基于自适应粒子群优化预测函数控制(APSO-PFC)的真空冻干温度控制方法,通过与PID控制方法的比较,以及对洋葱等真空冷冻干燥温度的动态跟踪控制表明,该方法优于原有的PID控制,实现了真空冷冻干燥温度的精确动态跟踪控制。

关键词: 真空冷冻干燥, 温度, 模型辨识, 智能预测控制

Abstract: In process of vacuum freeze-drying,the accurate control of freeze-drying temperature is a nonlinear dynamic tracking control problem.In practice,the freeze-drying temperature accurate dynamic tracking control is very difficult by PID controller.It influences physical chemical and biological performance and shape,particularly activity of biological product.These problems are solved by Predictive Functional Control(PFC) based on Adaptive Particle Swarm Optimization algorithm(APSO).These results of simulation and experiment show that the APSO-PFC has higher precision than the method of PID control.It is proved that this method is effective in the onion freeze-drying temperature accurate dynamic tracking control.

Key words: vacuum freeze-drying, temperature, model identification, intelligent predicting control

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