Identification of block-oriented nonlinear systems using orthonormal bases

Journal of Process Control

Volumn 14, Issue 6, 2004, Pages 685-697

  Gómez, Juan C ^a   Baeyens, Enrique ^b  

^a UNIVERSIDAD NACIONAL DE ROSARIO   (Argentina)

^b UNIVERSITY OF VALLADOLID   (Spain)

Author keywords

Block oriented models; Nonlinear identification; Process control; Singular value decomposition

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTER SIMULATION; ESTIMATION; IDENTIFICATION (CONTROL SYSTEMS); INVARIANCE; LINEAR CONTROL SYSTEMS; PROCESS CONTROL;

BLOCK-ORIENTED MODELS; NONLINEAR IDENTIFICATION; SINGULAR VALUE DECOMPOSITION;

NONLINEAR CONTROL SYSTEMS;

EID: 1842843133     PISSN: 09591524     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jprocont.2003.09.010     Document Type: Article

References (48)

1. Haber R., Unbehauen H. Structure identification of nonlinear dynamic systems - A survey on input/output approaches. Automatica. 26(4):1990;651-677.
2. Pearson R., Pottmann M. Gray-box identification of block-oriented nonlinear models. Journal of Process Control. 10:2000;301-315.
3. Eskinat E., Johnson S., Luyben W. Use of Hammerstein models in identification of nonlinear systems. AIChE Journal. 37(2):1991;255-268.
4. Greblicki W. Nonparametric identification of Wiener systems by orthogonal series. IEEE Transactions on Automatic Control. 39(10):1994;2077-2086.
5. Wigren T. Recursive prediction error identification using the nonlinear Wiener model. Automatica. 29(4):1993;1011-1025.
6. Wigren T. Convergence analysis of recursive identification algorithms based on the nonlinear Wiener model. IEEE Transactions on Automatic Control. 39(11):1994;2191-2206.
7. Pottmann M., Pearson R. Block-oriented NARMAX models with output multiplicities. AIChE Journal. 44:1998;131-140.
8. Kalafatis A., Arifin N., Wang L., Cluett W. A new approach to the identification of pH processes based on the Wiener model. Chemical Engineering Science. 50(23):1995;3693-3701.
9. C. Chou, H. Bloemen, V. Verdult, T. van den Boom, T. Backx, M. Verhaegen, Nonlinear identification of high purity distillation columns, in: Proceedings of the IFAC Symposium on System Identification SYSID 2000, Santa Barbara, CA, USA, June 2000, pp. 415-420.
10. M. Korenberg, Identification of biological cascades of linear and static nonlinear systems, in: Proceedings of the 16th Midwest Symposium on Circuit Theory, 1978, pp. 2.1-2.9.
11. Stapleton J., Bass S. Adaptive noise cancellation for a class of nonlinear dynamic reference channels. IEEE Transactions on Circuits and Systems. CAS-32:1985;143-150.
12. Fruzzetti K., Palazoglu A., McDonald K. Nonlinear model predictive control using Hammerstein models. Journal of Process Control. 7(1):1997;31-41.
13. Norquay S., Palazoglu A., Romagnoli J. Model predictive control based on Wiener models. Chemical Engineering Science. 53(1):1998;75-84.
14. Bloemen H., Chou C., van den Boom T., Verdult V., Verhaegen M., Backx T. Wiener model identification and predictive control for dual composition control of a distillation column. Journal of Process Control. 11:2001;601-620.
15. Narendra K., Gallman P. An iterative method for the identification of nonlinear systems using a Hammerstein model. IEEE Transactions on Automatic Control. AC-11:1966;546-550.
16. Billings S., Fakhouri S. Identification of nonlinear systems using correlation analysis. Proceedings IEE. 125:1978;691.
17. Billings S., Fakhouri S. Identification of a class of nonlinear systems using correlation analysis. Proceedings IEE, Corres. 125:1978;1307.
18. Billings S. Identification of nonlinear systems - A survey. Proceedings of IEE, Part D. 127:1980;272-285.
19. Billings S., Fakhouri S. Identification of systems containing linear dynamic and static nonlinear elements. Automatica. 18(1):1982;15-26.
20. Stoica P. On the convergence of an iterative algorithm used for Hammerstein system identification. IEEE Transactions on Automatic Control. AC-26(4):1981;967-969.
21. Boutayeb M., Darouach M. Recursive identification method for MISO Wiener-Hammerstein model. IEEE Transactions on Automatic Control. 40(2):1995;287-291.
22. Greblicki W., Pawlak M. Nonparametric identification of Hammerstein systems. IEEE Transactions on Information Theory. 35(2):1989;409-418.
23. Billings S., Fakhouri S. Identification of nonlinear systems using the Wiener model. Electronics Letters. 13:1978;502-504.
24. Khalil H. Nonlinear Systems. 1996;Prentice Hall, Englewood Cliffs, NJ.
25. Bai E. An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems. Automatica. 34(3):1998;333-338.
26. J.C. Gómez, E. Baeyens, Identification of multivariable Hammerstein systems using rational orthonormal bases, in: Proceedings of the 39th IEEE Conference on Decision and Control, Sydney, Australia, December 2000, pp. 2849-2854.
27. J.C. Gómez, Analysis of dynamic system identification using rational orthonormal bases, Ph.D. Thesis, The University of Newcastle, Australia, PS file downloadable from 〈http://www.fceia.unr.edu.ar/ ~jcgomez〉.
28. Ninness B., Gustafsson F. A unifying construction of orthonormal bases for system identification. IEEE Transactions on Automatic Control. AC-42(4):1997;515-521.
29. Wahlberg B. System identification using Laguerre models. IEEE Transactions on Automatic Control. AC-36(5):1991;551-562.
30. Wahlberg B. System identification using Kautz models. IEEE Transactions on Automatic Control. AC-39(6):1994;1276-1282.
31. Wahlberg B., Mäkilä P. On approximation of stable linear dynamical systems using Laguerre and Kautz functions. Automatica. 32(5):1996;693-708.
32. Van den Hof P., Heuberger P., Bokor J. System identification with generalized orthonormal basis functions. Automatica. 31(12):1995;1821-1834.
33. J.C. Gómez, E. Baeyens, Identification of nonlinear systems using orthonormal bases, in: Proceedings of the IASTED International Conference on Intelligent Systems and Control, Clearwater, FL, USA, November 2001, pp. 126-131.
34. M. Henson, D. Seborg, Nonlinear adaptive control of a pH neutralization process, in: Proceedings of the American Control Conference, 1992, pp. 2586-2590.
35. Henson M., Seborg D. Adaptive nonlinear control of a pH neutralization process. IEEE Transactions on Control Systems Technology. 2(3):1994;169-182.
36. Doyle F. III, Gatzke E., Parker R. Process Control Modules - A Software Laboratory for Control Design. International Series in the Physical and Chemical Engineering Sciences. 2000;Prentice Hall, Englewood Cliffs, NJ.
37. Sjöberg J., Zhang Q., Ljung L., Benveniste A., Delyon B., Glorennec P., Hjalmarsson H., Juditsky A. Nonlinear black-box modeling in system identification: a unified approach. Automatica. 31(12):1995;1691-1724.
38. Juditsky A., Hjalmarsson H., Benveniste A., Delyon B., Ljung L., Sjöberg J., Zhang Q. Nonlinear black-box modeling in system identification: mathematical foundations. Automatica. 31(12):1995;1725-1750.
39. S. Rangan, G. Wolodkin, K. Poolla, New results for Hammerstein system identification, in: Proceedings of the 34th IEEE Conference on Decision and Control, New Orleans, USA, December 1995, pp. 697-702.
40. Ljung L. System Identification: Theory for the User. second ed. 1999;Prentice-Hall, Inc. Englewood Cliffs, NJ.
41. Södeström T., Stoica P. System Identification. 1989;Prentice-Hall, Inc. Englewood Cliffs, NJ.
42. Golub G., Van Loan C. Matrix Computations. second ed. 1989;The Johns Hopkins University Press, Baltimore and London.
43. Maciejowski J. Predictive Control with Constraints. 2002;Prentice Hall.
44. Nonlinear process control. Henson M., Seborg D. Feedback Linearizing Control. 1997;Prentice Hall PTR, NJ. (Chapter 4).
45. W. Larimore, Canonical variate analysis in identification, filtering, adaptive control, in: Proceedings of the 29th Conference on Decision and Control, Honolulu, Hawaii, December 1990, IEEE, pp. 596-604.
46. L. Ljung, System Identification Toolbox, User's Guide, ver. 5, The MathWorks, Inc., Natick, MA, 2000.
47. Weischedel K., McAvoy T. Feasibility of decoupling in conventionally controlled distillation columns. Industrial and Engineering Chemical Fundamentals. 19(4):1980;379-384.
48. Luyben W., Tyréus B., Luyben M. Plantwide Process Control. 1999;McGraw Hill, New York.