A model-based predictive control scheme for steal rolling mills using neural networks

Journal of the Brazilian Society of Mechanical Sciences and Engineering

Volumn 25, Issue 1, 2003, Pages 85-89

  Galvez J M ^a   Zárate, Luis E ^b   Helman, H ^a  

^a FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^b PONTIFICAL CATHOLIC UNIVERSITY OF MINAS GERAIS   (Brazil)

Author keywords

Age systems; Model based predictive control; Neural networks; Steel industry

Indexed keywords

COMPUTER SIMULATION; IRON AND STEEL INDUSTRY; NEURAL NETWORKS; PREDICTIVE CONTROL SYSTEMS; SENSORS;

ROLL-GAP CONTROL;

ROLLING MILLS;

EID: 0038103086     PISSN: 16785878     EISSN: None     Source Type: Journal    
DOI: 10.1590/S1678-58782003000100012     Document Type: Article

References (19)

1. Alexander, J.M., 1972, "On the theory of Rolling." Proc. R. Soc. Lond. A. 326, pp. 535-563.
2. Andersen, K., Cook, G.E. and Barnett, R.J., 1992, "Gas Tungsten Arc Welding Process Control Using Artificial Neural Networks", International Trends in Welding, Science and Technology, ASM, pp. 877-1030.
3. Guez, A., Eilbert, J. L. and Kam, M., 1988, "Neural Network Architecture for Control", IEEE Control Systems Magazine, vol. 8, pp. 22-25.
4. Hunt, K.J., Sbarbaro, D., Zbikowski, R., and Gawthrop, P.J., 1992, "Neural Networks for Control", A Survey, Automatica, vol. 23, No. 6, pp. 1083-1112.
5. Khalid, M and Omatu, S., 1992, "A Neural Network Controller for a Temperature Control System", IEEE Control Systems, pp. 58-64.
6. Sbarbaro-Hofer, D., Neumerkel, D. and Hunt, K., 1993, "Neural Control of a Steel Rolling Mill", IEEE Control Systems, June, pp. 69-75.
7. Smartt, H.B., 1992, "Intelligent Sensing and Control of Arc Welding, International Trends in Welding", Science and Technology, ASM, pp. 843-851.
8. Tai, H. M., Wangi, J. and Ashenayi, K., 1992, "A Neural Network-Based Control System", IEEE Transactions on Industrial Electronics, vol. 39, no. 6, pp. 504-510.
9. Yamada, T., and Yabuta, T., 1993, "Dynamic System Identification Using Neural Networks", IEEE Transactions on Systems, Management, and Cybernetics, vol. 23, No.1.
10. Zárate, L.E., Helman, H., and Galvez, J.M., 1998, "Um Modelo para Processes de Laminação Baseado em Fatores de Sensibilidade", Utilizando RNA, Anais do IFAC-XII CBA.
11. Smith, O.J.M., 1957, "Closed Control of Loops with Dead Time, Chemical Engineering Process". (Vol., No., pp., se houver)
12. Garcia, C.E., Prett, D.M. and Morari, M., 1989, "Model Predictive Control: Theory and Practice - A Survey", Automatica, Vol. 25, No 3, pp. 335-348.
13. Ricker, N.L., 1991, "Model Predictive Control: State of the Art, Chemical Process Control", Fourth International Conference on Chemical Process Control, pp. 271-296, Amsterdam.
14. Morari, M. and Lee, J.H., 1991, "Model Predictive Control: The good, the bad and the ugly State of the Art", Fourth International Conference on Chemical Process Control, pp. 419-444, Amsterdam.
15. Muske, K.R. and Rawlings, J.B., 1993, "Model Predictive Control with Linear Models", AIChE Journal, Vol. 39, pp.262-287.
16. Rawlings, J.B., Meadows, E.S., and Muske, K.R., 1994, "Nonlinear Model Predicitve Control: A Tutorial and a Survey", ADCHEM'94 Proceedings, Kyoto, Japan.
17. Lee, J.H., Morari, M. and Garcia, C.E., 1994, "State Space Interpretation of Model Predictive Control", Automatica, Vol. 30, pp. 707-717.
18. Mayne, D.Q., 1996, "Nonlinear Model Predictive Control: An Assessment", Conference on Chemical Process Control, Tahoe City, California.
19. Zárate, Luis E., 1998, Um Método de Análise para Laminadores Tandem a Frio. Doctoral Thesis, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil.