A unified approach for the parametric identification of SISO/MIMO Wiener and Hammerstein systems

Journal of the Franklin Institute

Volumn 351, Issue 3, 2014, Pages 1717-1727

  Ikhouane, Fayçal ^a   Giri, Fouad ^b  

^a UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

^b UNIVERSITÉ DE CAEN   (France)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84894084442     PISSN: 00160032     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jfranklin.2013.12.016     Document Type: Article

References (26)

1. R.A. Adams, and J.J.F. Fournier Sobolev Spaces 2003 Elsevier
2. D. Bauer Asymptotic properties of subspace estimators Automatica 41 2005 359 376
3. S.I. Biagiola, and J.L. Figueroa Wiener and Hammerstein uncertain models identification Math. Comput. Simul. 79 2009 3296 3313
4. K.H. Chan, J. Bao, and W.J. Whiten Identification of MIMO Hammerstein systems using cardinal spline functions J. Process Control 16 2006 659 670
5. H.F. Chen Recursive identification for Wiener model with discontinuous piecewise linear function IEEE Trans. Autom. Control 51 3 2006 390 400
6. V. Cerone, and D. Regruto Parameter bounds for discrete-time Hammerstein models with bounded output errors IEEE Trans. Autom. Control 48 10 2003 1855 1860
7. P. Crama, and J. Schoukens Computing an initial estimate of a Wiener-Hammerstein system with a random phase multisine excitation IEEE Trans. Instrum. Meas. 54 2005 117 122
8. E.J. Dempsey, and D.T. Westwick Identification of Hammerstein models with cubic spline nonlinearities IEEE Trans. Biomed. Eng. 51 2 2004 237 245
9. G. Dolanc, and S. Strmčnik Identification of nonlinear systems using a piecewise-linear Hammerstein model Syst. Control Lett. 54 2 2005 145 158
10. M. Enqvist Identification of block-oriented systems using the invariance property F. Giri, E.-W. Bai, Block-Oriented Nonlinear System Identification 2010 Springer 149 159
11. F. Giri, and E.-W. Bai Block-Oriented Nonlinear System Identification, Lecture Notes in Control and Information Sciences 2010 Springer-Verlag Berlin
12. W. Greblicki, and M. Pawlak Nonparametric System Identification 2008 Cambridge University Press UK
13. F. Giri, Y. Rochdi, A. Brouri, and F.Z. Chaoui Parameter identification of Hammerstein systems containing backlash operators with arbitrary-shape parametric borders Automatica 47 2011 1827 1833
14. F. Giri, Y. Rochdi, and F.Z. Chaoui An analytic geometry approach to Wiener system frequency identification Trans. Autom. Control 54 4 2009 683 696
15. X. Jin Frequency domain analysis and identification of block-oriented nonlinear systems J. Sound Vib. 330 22 2011 5427 5442
16. A. Kalafatis, L. Wang, and W.R. Cluett Identification of time-varying pH processes using sinusoidal signals Automatica 41 2005 685 691
17. I.D. Landau, and G. Zito Digital Control Systems 2006 Springer-Verlag London
18. L. Ljung System Identification. Theory for the User second ed. 1999 Prentice Hall Upper Saddle River, NJ
19. S. Lakshminarayanan, S.L. Shah, and K. Nandakumar Identification of Hammerstein models using multivariate statistical tools Chem. Eng. Sci. 50 22 1995 3599 3613
20. K.S. Narendra, and P.G. Gallman An iterative method for the identification of nonlinear systems using a Hammerstein model IEEE Trans. Autom. Control July 1966 546 550
21. A.E. Nordsjö, and L.H. Zetterberg Identification of certain time-varying nonlinear Wiener and Hammerstein systems IEEE Trans. Signal Process. 49 3 2001 577 592
22. W. Rudin, Real and Complex Analysis, McGraw-Hill Series in Higher Mathematics, third ed., USA, 1987.
23. M. Rébillat, R. Hennequin, É. Corteel, and B.-F.G. Katz Identification of cascade of Hammerstein models for the description of nonlinearities in vibrating devices J. Sound Vib. 330 5 2011 1018 1038
24. H. Unbehauen, and G.P. Rao Continuous-time approaches to system identification - a survey Automatica 26 1 1990 23 35
25. M. Verhaegen Identification of the deterministic part of MIMO state space models given in innovations form from input-output data Automatica 30 1 1994 61 74
26. Y. Zhu Multivariable System Identification for Process Control 2001 Pergamon-Elsevier Oxford, UK