ニューラルネットワークによる化学プラントにおけるPIDゲイン調整システム Neural Network Based PID Gain Tuning of Chemical Plant Controller

この論文にアクセスする

この論文をさがす

著者

抄録

In these years, plant control systems are highly automated and applied to many industries. The control performances change with the passage of time, because of the deterioration of plant facilities. This is why human experts tune the control system to improve the total plant performances. In this study, PID control system for the oil refining chemical plant process is treated. In oil refining, there are thousands of the control loops in the plant to keep the product quality at the desired value and to secure the safety of the plant operation. According to the ambiguity of the interference between control loops, it is difficult to estimate the plant dynamical model accurately. Using neuro emulator and recurrent neural networks model (RNN model) for emulation and tuning parameters, PID gain tuning system of chemical plant controller is constructed. Through numerical experiments using actual plant data, effect of the proposed method was ascertained.

収録刊行物

  • 電気学会論文誌. D, 産業応用部門誌 = The transactions of the Institute of Electrical Engineers of Japan. D, A publication of Industry Applications Society

    電気学会論文誌. D, 産業応用部門誌 = The transactions of the Institute of Electrical Engineers of Japan. D, A publication of Industry Applications Society 128(7), 940-947, 2008-07-01

    The Institute of Electrical Engineers of Japan

参考文献:  11件中 1-11件 を表示

被引用文献:  3件中 1-3件 を表示

各種コード

  • NII論文ID(NAID)
    10021134847
  • NII書誌ID(NCID)
    AN10012320
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    09136339
  • NDL 記事登録ID
    9564514
  • NDL 雑誌分類
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL 請求記号
    Z16-1608
  • データ提供元
    CJP書誌  CJP引用  NDL  J-STAGE 
ページトップへ