Model reduction for process control using iterative nonlinear identification

Proceedings of the American Control Conference

Volumn 4, Issue , 2004, Pages 2915-2920

  Vargas, Alejandro ^a   Allgöwer, Frank ^a  

^a UNIVERSITY OF STUTTGART   (Germany)

Author keywords

Copolymerization; Generalized basis functions; Input optimization; System identification; Volterra systems

Indexed keywords

COPOLYMERIZATION; FUNCTIONS; IDENTIFICATION (CONTROL SYSTEMS); ITERATIVE METHODS; NONLINEAR CONTROL SYSTEMS; OPTIMIZATION;

GENERALIZED BASIS FUNCTIONS; INPUT OPTIMIZATION; NONLINEAR IDENTIFICATION; VOLTERRA SYSTEMS;

PROCESS CONTROL;

EID: 8744277386     PISSN: 07431619     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.23919/acc.2004.1384354     Document Type: Conference Paper

References (23)

1. B. Ogunnaike and W. Ray, Process Dynamics, Modeling, and Control. New York: Oxford University Press, 1996.
2. L. Ljung, System Identification. Theory for the user, 2nd ed. Upper Saddle River: Prentice-Hall, 1999.
3. O. Nelles, Nonlinear System Identification. Berlin: Springer, 2001.
4. R. Pintelon and J. Schoukens, System Identification. A frequency domain approach. Piscataway: IEEE Press, 2001.
5. M. Schetzen, The Volterra and Wiener Theories of Nonlinear Systems. New York: John Wiley & Sons, 1980.
6. F. Doyle III, R. Pearson, and B. Ogunnaike, Identification and Control Using Volterra Models. London: Springer, 2002.
7. B. Ninness, H. Hjalmarsson, and F. Gustafsson, "The fundamental role of general orthonormal bases in system identification," IEEE Trans. Automatic Control, vol. 44, no. 7, pp. 1384-1406, 1999.
8. S. Chen, S. Billings, and W. Luo, "Orthogonal least squares methods and their application to nonlinear identification," Int. J. Control, vol. 50, no. 5, pp. 1873-1896, 1989.
9. S. Chen, X. Hong, and C. Harris, "Sparse kernel regression modelling using combined locally regularized orthogonal least squares and D-optimality experimental design," IEEE Trans. Automatic Control, vol. 48, no. 6, pp. 1029-1036, 2003.
10. A. Kibangou, G. Favier, and M. Hassani, "Generalized orthonormal basis selection for expanding quadratic Volterra filters," in Proc. 13th IFAC Symposium on System Identification, Rotterdam, The Netherlands, July 2003, pp. 1119-1124.
11. C. Lesiak and A. Krener, "The existence and uniqueness of Volterra series for nonlinear systems," IEEE Trans. Automatic Control, vol. 23, no. 6, pp. 1090-1095, 1978.
12. S. Boyd and L. Chua, "Fading memory and the problem of approximating nonlinear operators with Volterra series," IEEE Trans. Cir. Sys., vol. 32, no. 11, pp. 1150-1161, 1985.
13. B. Ninness and F. Gustafsson, "A unifying construction of orthonormal bases for system identification," IEEE Trans. Automatic Control, vol. 42, no. 4, pp. 515-521, 1997.
14. C. Seretis and E. Zafiriou, "Nonlinear dynamical system identification using reduced Volterra models with generalized orthonormal basis functions," in Proc. American Control Conference, Albuquerque, New Mexico, June 1997, pp. 3042-3046.
15. J. Gómez, "Analysis of dynamic system identification using rational orthonormal bases," Ph.D. dissertation, The University of Newcastle, Australia, 1998, available at www.fceia.unr.edu.ar/~jcgomez.
16. J. Schoukens, T. Dobrowiecki, and R. Pintelon, "Parametric and nonparametric identification of linear systems in the presence of nonlinear distortions - A frequency domain approach," IEEE Trans. Automatic Control, vol. 43, no. 2, pp. 176-190, 1998.
17. T. McKelvey, H. Akcay, and L. Ljung, "Subspace-based multivariable system identification from frequency response data," IEEE Trans. Automatic Control, vol. 41, no. 7, pp. 960-979, 1996.
18. C. Evans, D. Rees, L. Jones, and M. Weiss, "Periodic signals for measuring nonlinear Volterra kernels," IEEE Trans. Instrum. Meas., vol. 45, no. 2, pp. 362-371, 1996.
19. R. Haber and H. Unbehauen, "Structure identification of nonlinear dynamic systems - a survey on input/output approaches," Automatica, vol. 26, no. 4, pp. 651-677, 1990.
20. H. Akaike, "A new look at the statistical model identification, " IEEE Trans. Automatic Control, vol. 19, no. 6, pp. 716-723, 1974.
21. L. Aguirre and S. Billings, "Improved structure selection for nonlinear models based on term clustering," Int. J. Control, vol. 62, no. 3, pp. 569-587, 1995.
22. R. Bindlish, "Modeling and control of polymerization processes," Ph.D. dissertation, University of Wisconsin, Madison, 1999.
23. R. Pearson, "Input sequences for nonlinear modeling," in Nonlinear Model Based Process Control, ser. NATO AST, R. Berber and C. Kravaris, Eds. Dordrecht: Kluwer Academic Publishers, 1998, no. 353, pp. 599-621.