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    National Tsing Hua University Institutional Repository > 工學院  > 化學工程學系 > 期刊論文 >  Optimal multiloop feedback design using simulated annealing and neural network

    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/37960

    Title: Optimal multiloop feedback design using simulated annealing and neural network
    Authors: Lin,Julian Jeng Lin;Wong,David Shan Hill;Yu,Shuh Woei
    教師: 汪上曉
    Date: 1995
    Publisher: John Wiley & Sons
    Relation: AICHE JOURNAL, John Wiley & Sons, Volume 41, Issue 2, FEB 1995, Pages 430-434
    Keywords: Control systems
    Feedback control
    Simulated annealing
    Neural networks
    Abstract: ©1995 Wiley - In this study, artificial neural network is utilized directly for feedback control system design. A neural network is trained on-line to learn the complex and highly nonlinear relationship between tuning parameters, process upsets, and the summation of time-weighted absolute error integrals of the quality control loops of a simulated high-purity distillation column. With the learning process directed by simulated annealing, the number of test runs can be greatly reduced. Optimal tuning parameters are obtained using the ANN model. Satisfactory control of both end products of the binary column is maintained with the proposed design technique.
    URI: http://www.wiley.com/
    Appears in Collections:[化學工程學系] 期刊論文

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