ID | 46978 |
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Sort Key | 5
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FullText URL | |
Author |
Imajo, Shuya
Konishi, Masami
Imai, Jun
Kaken ID
researchmap
Nishi, Tatsushi
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Abstract | 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.
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Publication Title |
Memoirs of the Faculty of Engineering, Okayama University
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Published Date | 2003-03
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Volume | volume37
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Issue | issue2
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Publisher | Faculty of Engineering, Okayama University
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Start Page | 29
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End Page | 44
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ISSN | 0475-0071
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NCID | AA10699856
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Content Type |
Departmental Bulletin Paper
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OAI-PMH Set |
岡山大学
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language |
English
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File Version | publisher
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NAID | |
Eprints Journal Name | mfe
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