Multivariable predictive control of a pressurized tank using neural networks

Neural Computing and Applications

Volumn 15, Issue 1, 2006, Pages 18-25

  Duarte Mermoud, Manuel A ^a   Suárez, Alejandro M ^b   Bassi, Danilo F ^c  

^a UNIVERSITY OF CHILE   (Chile)

^b DEPARTAMENTO DE FÍSICA   (Chile)

^c UNIVERSIDAD DE SANTIAGO DE CHILE   (Chile)

Author keywords

Adaptive neural control; Adaptive neural network control; Control of pressurized tank; Multivariable control; Neural control; Predictive neural control

Indexed keywords

EID: 28344448717     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-005-0003-0     Document Type: Article

References (32)

1. Narendra KS, Parthasarathy K (1990) Identification and control of dynamical systems using neural networks. IEEE Trans Neural Networ 1:4-27
2. Narendra KS, Parthasarathy K (1991) Gradient methods for optimization of dynamical systems containing neural networks. IEEE Trans Neural Networ 2:252-262
3. Hornik K, Stincombe M, White H (1990) Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks. Neural Networ 3:211-223
4. Draeger A, Engell S, Ranke H (1995) Model predictive control using neural networks. IEEE Contr Syst Mag 15(5):61-66
5. Murray-Smith R, Sbarbaro D, Neumerkel D (1992) Neural networks for modeling and control of a nonlinear dynamic system. In: IEEE symposium on intelligent control, Glasgow, Scotland pp 122-127
6. Hyaline S (1999) Neural networks: a comprehensive foundation. Prentice Hall, New Jersey
7. Cutler C, Ramaker B (1980) Dynamic matrix control: a computer control algorithm". In: Proceedings of the joint automatic control conference, San Francisco, CA Paper WP5-B
8. Garcia CE, Morari M (1982) Internal model control. A unifying review and some new results. Ind Eng Chem Process Des Dev 21:308-323
9. Peterson T, Hernandez E, Arkun Y, Schork FJ (1989) Nonlinear predictive control of a semi batch polymerization reactor by an extended DMC. In: Proceedings of the 1989 American Control Conference, Pittsburgh, PA, pp 1534-1539
10. Brengel DD, Seider WD (1989) Multistep nonlinear predictive control. Ind Chem Eng Res 28:1812-1822
11. Bordons AC, Camacho E (1998) A generalized predictive controller for a wide class of industrial processes. IEEE Trans Contr Syst Technol 6:372-387
12. Thibaut J, Grandjean (1992) Neural networks in process control: a survey. In: Najim K, Dufour E (eds) Advanced control of chemical processes. IFAC Symposium Series No. 8 pp 251-260
13. MacMurray J, Himmelblau D (1993) Identification of a packed distillation column for control via artificial neural networks. In: Proceedings of the 1993 American control conference, San Francisco, CA, pp 1455-1459
14. Zamarreño JM, Vega P (1996) Neural predictive control: Application to a highly non linear process. In: Proceedings of the 13 IFAC world congress, San Francisco, USA Vol. C, Control Design I, 1996, pp 19-24
15. Jazayeri-Rad H (2004) The nonlinear model-predictive control of a chemical plant using multiple neural networks. Neural Comput Appl 13(1):2-15
16. Chu JZ, Tsai PF, Tsai WY et al. (2003) An experimental study of model predictive control based on artificial neural networks. Lect Notes Artif Intell 2773:1296-1302
17. Santos VML, Carvalho FR, de Souza MB (2000) Predictive control based on neural networks: an application to a fluid catalytic cracking industrial unit. Brazil J Chem Eng 17(4-7):897-905
18. Kovarova-Kovar K, Gehlen S, Kunze A et al. (2000) Application of model-predictive control based on artificial neural networks to optimize the fed-batch process for riboflavin production. J Biotechnol 79(1):39-52
19. Galvan IM, Zaldivar JM (1998) Application of recurrent neural networks in batch reactors - Part II: Nonlinear inverse and predictive control of the heat transfer fluid temperature. Chem Eng Process 37(2):149-161
20. Peligrad AA, Zhou E, Morton D et al. (2002) System identification and predictive control of laser marking of ceramic materials using artificial neural networks. In: Proceedings of the Institution of Mechanical Engineers Part I-Journal of Systems and Control Engineering 216(I2):181-190
21. Liu GP, Daley S (1999) Output-model-based predictive control of unstable combustion systems using neural networks. Contr Eng Pract 7(5):91-600
22. Meghlaoui A, Bui RT, Thibault J et al. (1998) Predictive control of aluminum electrolytic cells using neural networks. Metall Mater Trans B-Process Metall Mater Process Sci 29(5):1007-1019
23. Chu JZ, Tsai PF, Tsai WY et al (2003) Multistep model predictive control based on artificial neural networks. Indust Eng Chem Res 42(21):5215-5228
24. Tsai PF, Chu JZ, Jang SS et al (2003) Developing a robust model predictive control architecture through regional knowledge analysis of artificial neural networks. J Process Contr 13(5):423-435
25. Wang LX, Wan F (2001) Structured neural networks for constrained model predictive control. Automatica 37(8):1235-1243
26. Piche S, Sayyar-Rodsari B, Johnson D et al (2000) Nonlinear model predictive control using neural networks. IEEE Contr Syst Mag 20(3):53-62
27. Liu GP, Kadirkamanathan V, Billings SA (1998) Predictive control for non-linear systems using neural networks. Int J Contr 71(6):1119-1132
28. Rusnak A, Fikar M, Najim K et al (1996) Generalized predictive control based on neural networks. Neural Process Lett 4(2):107-112
29. AM Suárez (1998) Nueva arquitectura de control predictivo para sistemas dinámicos nolineares usando redes neuronales. Tesis de Doctorado en Ciencias de la Ingeniería, Mención Automática. Depto. de Ing. Eléctrica, U. de Chile, Santiago, Chile
30. Suárez AM, Duarte-Mermoud MA, Bassi DF (2005) A predictive control scheme based on neural networks. Kybernetes 34 (in press)
31. Eggimann MA, Crisalle OD, Longchamp R (1992) A linear-programming predictive controller with variable horizon. Proceedings of the 1992 American Control Conference, Chicago, II, pp 1568-1575
32. Soto JM, Sbarbaro D (1998) Dynamically synthesized variable structure controller with integral modes. In: Proceedings of the American control conference, Pennsylvania, PA, pp 584-588