Nonlinear system identification of block-oriented systems using local affine models

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 15, Issue PART 1, 2009, Pages 658-663

  Zimmerschied, Ralf ^a   Isermann, Rolf ^a  

^a DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

Global local regularization; Hammerstein model; Local affine model; LOLIMOT; Nonlinear system identification; Wiener model

Indexed keywords

AFFINE MODEL; GLOBAL-LOCAL; HAMMERSTEIN MODEL; LOLIMOT; NON-LINEAR SYSTEM IDENTIFICATION; WIENER MODELS;

GLOBAL OPTIMIZATION; MATHEMATICAL OPERATORS; OPTIMIZATION;

NONLINEAR SYSTEMS;

EID: 80051637224     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3182/20090706-3-FR-2004.0018     Document Type: Conference Paper

References (16)

1. J. Abonyi, R. Babuška, M. Ayala Botto, F. Szeifert, and L. Nagy. Identification and control of nonlinear systems using fuzzy hammerstein models. Industrial and Engineering Chemistry Research, 39:4302-4314, 2000.
2. L. A. Aguirre, M. C. S. Coelho, and M. V. Corrêa. On the interpretation and practice of dynamical differences between hammerstein and wiener models. IEE Proceedings on Control Theory and Applications, 152(4):349-356, 2005. (Pubitemid 41048198)
3. I. Goethals, K. Pelckmans, J.A.K. Suykens, and B. De Moor. Subspace identification of Hammerstein systems using least squares support vector machines. IEEE Transactions on Automatic Control, 50(10):1509-1519, 2005. (Pubitemid 41555601)
4. Rolf Isermann. Identifikation dynamischer Systeme 2. Springer-Verlag, Berlin, 1992.
5. Rolf Isermann, Susanne Ernst, and Oliver Nelles. Identification with dynamic neural networks - architectures, comparisions, applications - plenary. In IFAC Symposium on System Identification, pages 997-1022, Fukuoka, Japan, 1997.
6. Andrzej Janczak. Identification of Nonlinear Systems Using Neural Networks and Polynomial Models - A Block-Oriented Approach. Springer-Verlag, 2005.
7. Lennart Ljung. System Identification - Theory for the User. Prentice Hall, Englewood Cliffs, 1999.
8. J. E. Moody. The effective number of parameters: An analysis of generalization and regularization in nonlinear learning systems. In J. E. Moody, S. J. Hanson, and R. P. Lippmann, editors, Advances in Neural Information Processing Systems 4, pages 847-854. Morgan Kaufmann Publishers, San Mateo, USA, 1992.
9. Jorge J. Moré. The Levenberg-Marquardt algorithm: Implementation and theory. In G.A. Watson, editor, Numerical Analysis, volume 630 of Lecture Notes in Mathematics, pages 105-116. Springer-Verlag, 1978.
10. Roderick Murray-Smith and Tor Arne Johansen. Local learning in local model networks. In Roderick Murray-Smith and Tor Arne Johansen, editors, Multiple Model Approaches to Modelling and Control, pages 185-210. Taylor & Francis Ltd., London, 1997a.
11. Roderick Murray-Smith and Tor Arne Johansen, editors. Multiple Model Approaches to Modelling and Control. Taylor & Francis, 1997b.
12. Oliver Nelles. Nonlinear System Identification. Springer-Verlag, Berlin, 2001.
13. Oliver Nelles, Alexander Fink, and Rolf Isermann. Local linear model trees (LOLIMOT) toolbox for nonlinear system identification. In Proceesdings of the 12th IFAC Symposium on System Identification (SYSID 2000), Santa Barbara, USA, 2000.
14. Andrey N. Tikhonov and Vasiliy Y. Arsenin. Solutions of ill-posed problems. John Wiley & Sons, 1977.
15. Ralf Zimmerschied. Identification of nonlinear processes using dynamic local-affine models - Techniques for reduction of bias and variance (in german). Number 1150 in Fortschritt-Berichte VDI, Series 8. VDI Verlag, Düsseldorf, 2008.
16. Ralf Zimmerschied and Rolf Isermann. Regularization techniques for identification using local-affine models (in german). at - Automatisierungstechnik, 56(7):339-349, 2008.