Gain Tuning Model of Human Expert for Looper Height Control in Hot Strip Rolling

• Imajo Shuya

• Konishi Masami

• Imai Jun

• Nishi Tatsushi

抄録

In hot strip rolling mills, the looper control system is automated. However, the looper's behavior tends to be unstable in threading. Therefore, human expert always intervenes and stabilizes the looper's behavior by tuning PID gains and interposing manipulation variable of looper control system. In this paper, we propose a method based on the recurrent neural network to express PID gains tuning action by human. Furthermore, we propose two methods to update the model by learning. To check the effectiveness of the proposed learning methods, numerical simulation applied to the looper height control is carried out.

収録刊行物

• Memoirs of the Faculty of Engineering, Okayama University

  Memoirs of the Faculty of Engineering, Okayama University 37 (2), 29-44, 2003-03

  Faculty of Engineering, Okayama University

詳細情報

• CRID: 1390009224822818816
• NII論文ID: 80016037880
• NII書誌ID: AA10699856
• ISSN: 04750071
• DOI: 10.18926/46978
• Web Site: https://ousar.lib.okayama-u.ac.jp/46978
• 本文言語コード: en
• データソース種別:
  • JaLC
  • IRDB
  • CiNii Articles