Neural network based diagnosis system for looper height controller of hot strip mills

International Journal of Innovative Computing, Information and Control

Volumn 3, Issue 4, 2007, Pages 919-935

  Abe, Yoshihiro ^a   Konishi, Masami ^a   Imai, Jun ^a  

^a OKAYAMA UNIVERSITY   (Japan)

Author keywords

Hierarchical neural network (HNN); Hot strip rolling; Looper height control; Neural network emulator (Neuro emulator); PID control; Recurrent neural network (RNN)

Indexed keywords

EID: 63549107108     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (10)

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2. Asada, S. H. et al., Adaptive and robust control-method with estimation of rolling characteristics for looper angle control at hot strip mill, ISIJ International, vol.43, no.3, pp358-365, 2003.
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5. Imajo, S. et al., Human model for gain tuning of looper control in hot strip rolling, Tetsu-to-Hagane, vol.90, no.ll, pp.933-940, 2004.
6. Asano, K. et al., Parameters estimation for the tension model in hot strip mills, IFCA, pp.319-324, 2001
7. Torigoe, T. et al., Faukt diagnosis of looper height control system by neural network, SICE Annual Conference, pp.996-1001, 2005.
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9. Omatu, S. et al., Self-tuning nruro-pid control and applidations, IEEE Conference Proceeding, pp.1985-1989, 1997.
10. Sato, T. et al., Improvement of tracking performance in self-tuning pid controller based generalized predictive control, International Journal of Innovative Computing, Information and Control, vo.2, no.3, pp.491-503, 2006.