제어로봇시스템학회논문지 (Journal of Institute of Control, Robotics and Systems)

  • 제13권4호
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  • Pages.296-303
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  • 2007
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  • 1976-5622(pISSN)
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  • 2233-4335(eISSN)
제어로봇시스템학회 (Institute of Control, Robotics and Systems)
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신경회로망과 퍼지 논리를 이용한 열간 사상압연 폭 예측 모델 및 제어기 개발

Width Prediction Model and Control System using Neural Network and Fuzzy in Hot Strip Finishing Mills

  • 황이철 (동의대학교 메카트로닉스 공학과) ;
  • 박철재 (포스코 기술연구소)
  • 발행 : 2007.04.01
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초록

This paper proposes a new width control system composed of an ANWC(Automatic Neural network based Width Control) and a fuzzy-PID controller in hot strip finishing mills which aims at obtaining the desirable width. The ANWC is designed using a neural network based width prediction model to minimize a width variation between the measured width and its target value. Input variables for the neural network model are chosen by using the hypothesis testing. The fuzzy-PlD control system is also designed to obtain the fast looper response and the high width control precision in the finishing mill. It is shown through the field test of the Pohang no. 1 hot strip mill of POSCO that the performance of the width margin is considerably improved by the proposed control schemes.

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참고문헌

  1. T. Shibahara, 'Edger set-up model at roughing train in hot strip mill,' ISIJ, vol. 67, no. 15, pp. 2509-2515, 1981
  2. T. Sasaki, 'Mathematical model of width change in the hot strip finishing train,' CAMPISIJ, vol. 9, pp. 304-307, 1996
  3. K. Yamada, S. Ogawa, and M. Ataka, 'Three dimensional analysis of at rolling using rigid-plastic finite element method coupled with roll deformation analysis,' NUMIFORM92, pp. 755-760, 1992
  4. lsii, 'Analysis of width deviation for hot strip finishing mill,' Japan Society for Technology of Plasticity, pp. 219-222, 1992
  5. C. J. Park and D. M. Lee, 'Input selection technology of neural network and its application for hot strip mill,' IFAC World Congress, 2005
  6. A. Hacquin and P. Montmitonnet, 'Coupling of roll and strip deformation in three-dimensional simulation of hot rolling,' Simulation of Mat. Proc., pp. 921-927, 1995
  7. A. Helmi and J. Alexander, 'Geometric factors affecting spread in hot at rolling of steel,' JISI, no. 206, pp. 1110-1117, 1968
  8. A. Ishii, 'Variation of strip width during hot finishing rolling,' CAMP-ISIJ, vol. 9, pp. 300-303, 1996
  9. J. Price, 'The hot strip mill looper system,' IEEE Transactions on Industry Applications, vol. IA-9, no. 5, pp. 556-562, 1973 https://doi.org/10.1109/TIA.1973.349940
  10. A. Mizuta, H. Ibata, Y. Yamamoto, S. Saito, S. Honda, and M. Kitamura, 'Control method and its performance,' Transactions of the Iron and Steel Institute of Japan, vol. 26, p. B21, 1986
  11. D. A. Davies, 'Application of hydraulic agc and width control to a hot strip mill,' Iron and Steel Engineer, vol. 66, no. 8, pp. 39-44,1989
  12. Anon, 'A new roll force awc system for roughing train in hot strip mill,' Transactions of the Iron and Steel Institute of Japan, vol. 27, no. 12, p. 993, 1987 https://doi.org/10.2355/isijinternational1966.27.993
  13. S. Nakamura, M. Takahashi, and Y. Chida, 'Slab width control for hot direct rolling,' Transactions of the Iron and Steel Institute of Japan, vol. 28, pp. 110-116, 1988 https://doi.org/10.2355/isijinternational1966.28.110
  14. H. Yoneda, 'Development of accurate width control technology in hot strip finishing mill,' CAMP-ISIJ, vol. 9, pp. 312-315, 1996
  15. T. Ogura, 'Advanced width control for hot finishing mill,' CAMP-lSIJ, vol. 9, p. 324, 1996
  16. S. Murata, 'Development of width control technology in finishing line of hot strip mill,' CAMP-ISIJ, vol. 9, pp. 308-311, 1996
  17. H. Senda, 'Development of the width control system in no.3 hot strip mill at Chiba Works,' CAMP-ISIJ, vol. 11, p. 356, 1998
  18. T. Takahara, 'Improvement of width accuracy in Fukuyama no.1 hot strip mill,' CAMPISIJ, vol. 10, p. 391, 1997
  19. JISF, The theory and practice of the steel rolling. JISF, 1983
  20. S. Kunimatsu, T. Fujii, and T. Tsujino, 'Quadratic stabilization of lLQ servo systems with generalized reference inputs,' T. SICE, vol. 39, no. 3, pp. 307-309, 2003 https://doi.org/10.9746/sicetr1965.39.307
  21. H. lmanari, Y. Morimatsu, K. Sekiguchi, H. Ezure, R. Matuoka, A. Tokuda, and H. Otobe, 'Looper H-Infinity control for hot strip mills,' IEEE Transactions on Industry Applications, vol. 33, no. 3, pp. 790-796, 1997 https://doi.org/10.1109/28.585871
  22. J. W. Lee, W. H. Kwon, and J. H. Choi, 'On stability of constrained receding horizon control with finite terminal weighting matrix,' Automatica, vol. 34, no. 12, pp. 1607-1612, 1998 https://doi.org/10.1016/S0005-1098(98)80015-0
  23. D. Yu, J. Gomm, and D. Williams, 'Neural model input selection for a mimo chemical process,' Engineering Applications of Artificial intelligence, vol. 13, pp. 15-23, 2000 https://doi.org/10.1016/S0952-1976(99)00046-9
  24. W. Wu and D. Massart, 'Artificial neural networks in classification of NIR spectral data : Selection of the input,' Chemometrics and Intelligent Laboratory Systems, vol. 35, pp. 127-135,1996 https://doi.org/10.1016/S0169-7439(96)00034-2
  25. A. Back and T. Trappenberg, 'Selecting inputs for modeling using normalized higher order statistics and independent component analysis,' IEEE Transactions on Neural Networks, vol. 12, no. 3, pp. 612-617, 2001 https://doi.org/10.1109/72.925564
  26. C. Ledoux and J. Grandin, 'Two original weight pruning methods based on statistical tests and rounding techniques,' lEE Proc. Vision, Image Signa! Process. vol. 141, no. 4, pp. 230-236, 1994 https://doi.org/10.1049/ip-vis:19941328
  27. R. Reed, 'Pruning algorithms: a survey,' IEEE Trans. Neural Netw. , vol. 4, no. 5, pp. 740-747, 1993 https://doi.org/10.1109/72.248452
  28. J. Luo, B. Hu, X. Ling, and R, Liu, 'Principal independent component analysis,' IEEE Transactions on Neural Networks, voI. 10, no. 4,pp.912-917,1999 https://doi.org/10.1109/72.774259
  29. N. Kambhatla and T. Leen, 'Dimension reduction by local principal component analysis,' Neural Comput., vol. 9, no. 7, pp. 1493-1516,1997 https://doi.org/10.1162/neco.1997.9.7.1493
  30. S. Ross, Introduction to Probability and Statistics for Engineers and Scientists, Academic Press, 2000
  31. S. Z. He, 'Fuzzy self-tuning of PID controller,' Fuzzv Sets and Systems, pp. 37-46,1993