CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Identification of MIMO Hammerstein models using Singular Value Decomposition approach

by Badreddine Louhichi, Ahmed Toumi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 42 - Number 9
Year of Publication: 2012
Authors: Badreddine Louhichi, Ahmed Toumi
10.5120/5723-7783

Badreddine Louhichi, Ahmed Toumi . Identification of MIMO Hammerstein models using Singular Value Decomposition approach. International Journal of Computer Applications. 42, 9 ( March 2012), 29-37. DOI=10.5120/5723-7783

@article{ 10.5120/5723-7783,
author = { Badreddine Louhichi, Ahmed Toumi },
title = { Identification of MIMO Hammerstein models using Singular Value Decomposition approach },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 42 },
number = { 9 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 29-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume42/number9/5723-7783/ },
doi = { 10.5120/5723-7783 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:32:07.150123+05:30
%A Badreddine Louhichi
%A Ahmed Toumi
%T Identification of MIMO Hammerstein models using Singular Value Decomposition approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 42
%N 9
%P 29-37
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we present a new approach to identify multivariable Hammerstein systems based on the Singular Value Decomposition (SVD) method. The technique allows for the determination of the memoryless static nonlinearity as well as the estimation of the model parameters of the dynamic Auto-Regressive model with eXogenous input (ARX) part. First of all, an iteration procedure is proposed to identify the parameters of Multi-Input Multi-Output (MIMO) Hammerstein models by using the Recursive Least Squares (RLS) algorithm. Secondly, the obtained parameter estimates of the identification model include the product terms of the parameters of the original systems. So, to separate these parameters of the original parameters from the product terms, the singular value decomposition method is discussed. Finally, a simulation study is performed to demonstrate the effectiveness of the proposed method compared with the existing approaches.

References
  1. Abonyi, J. , Babuska, R. , Botto, M. a. , Szeifert, F. And Nagy, L. , (2000) "identification And Control Of Nonlinear Systems Using Fuzzy Hammerstein Models". Ind Eng Chem Res, 39 Pp. 4302 – 4314.
  2. Al-duwaish, H. And Karim, M. n. , (1997) "a New Method For The Identification Of Hammerstein Model". Automatica 33 Pp. 1871 – 1875.
  3. Bai, E. W. , (1998) "an Optimal Two-stage Identification Algorithm For Hammerstein–wiener Nonlinear Systems". Automatica, 34 (3), Pp. 333 – 338.
  4. Bai, E. w. , (2004) "decoupling The Linear And Nonlinear Parts In Hammerstein Model Identification", Automatica 40 (4) Pp. 671 – 676.
  5. Chaoui, F. z. , Giri, F. , Rochdi, Y. , Haloua, M. , And Naitali, A. , (2005) "system Identification Based On Hammerstein Model", International Journal Of Control 78 (6) Pp. 430 – 442.
  6. Ding, F. And Chen, T. , (2005) "identification Of Hammerstein Nonlinear Armax Systems", Automatica 41 (9) Pp. 1479 – 1489.
  7. Ding, F. , Shi, Y. And Chen, T. , (2006) "gradient-based Identification Methods For Hammerstein Nonlinear Armax Models", Nonlinear Dynamics 45 (1_2) Pp. 31 – 43.
  8. Ding, F. , Shi, Y. And Chen, T. , (2007) "auxiliary Model Based Least-squares Identification Methods For Hammerstein Output-error Systems", Systems & Control Letters 56 (5) Pp. 373 – 380.
  9. Ding, F. , Chen, T. And Iwai, Z. , (2007) "adaptive Digital Control Of Hammerstein Nonlinear Systems With Limited Output Sampling", Siam Journal On Control And Optimization 45 (6) Pp. 2257 – 2276.
  10. Ding, F. , Peter, L. X. , And Liu, G. , (2011) "identification Methods For Hammerstein Nonlinear Systems", Digital Signal Processing 21 Pp. 215 – 238.
  11. Hlaing Y. m. , Chiu M. -s. And Lakshminarayanan S. , (2007) "modeling And Control Of Multivariable Process Using Generalized Hammerstein Model". Chemical Engineering Research And Design Trans, Vol 85 (a4) Pp. 445 – 454.
  12. Hua Liang And Bolin Wang, (2007) "identification Of Mimo Hammerstein Models Using Support Vector Machine". Isnn 2007, Part Iii, Lncs 4493, Pp. 399 – 406. Springer-verlag Berlin Heidelberg.
  13. Ivan Goethals, Kristiaan Pelckmans, Johan A. k. Suykens, Bart De Moor, (2005) "identification Of Mimo Hammerstein Models Using Least Squares Support Vector Machines". Automatica 41 Pp. 1263 – 1272.
  14. Jia, L. , Chiu, M. s. And Ge, S. s. , (2005) "iterative Identification Of Neuro-fuzzy Based Hammerstein Model With Global Convergence". Ind Eng Chem Res, 44 Pp. 1823 – 1831.
  15. Jia L. , Chiu M. s. , Ge S. s. , (2005) "a Noniterative Neuro-fuzzy Based Identification Method For Hammerstein Processes", Journal Of Process Control 15 (7) Pp. 749 – 761.
  16. Juan C. Gomez, Enrique Baeyens, (2004) "identification Of Block-oriented Nonlinear System Using Orthonormal Bases", Journal Of Process Control 14 Pp. 685 – 697.
  17. Jyothi S. N. , Chidambaram M. , (2000) "identification Of Hammerstein Model For Bioreactors With Input Multiplicities". Bioprocess Engineering 23 Pp. 323 – 326 Springer-verlag.
  18. Kwong Ho Chan, Jie Bao, William J. Whiten, (2006) "identification Of Mimo Hammerstein Systems Using Cardinal Spline Functions". Journal Of Process Control 16 Pp. 659 – 670.
  19. Lakshminarayanan, S. , Shah, S. L. , & Nandakumar, K. (1995) "identification Of Hammerstein Models Using Multivariate Statistical Tools". Chemical Engineering Science, 50 (22), Pp. 3599 – 3613.
  20. Lee, M. w. , Huang, H. p. And Jeng, J. c. , (2004) "identification And Controller Design For Nonlinear Processes Using Relay Feedback". J Chem Eng Japan, 37 Pp. 1194 – 1206.
  21. Lee Y. j. , Sung S. w. , Park S. , (2005) "input Test Signal Design And Parameter Estimation Method For The Hammerstein–wiener Processes", Industrial And Engineering Chemistry Research 43 (23) Pp. 7521 – 7530.
  22. Liu, Y. , Sheng, J. , And Ding, R. , (2010) "convergence Of Stochastic Gradient Estimation Algorithm For Multivariable Arx-like Systems", Computers And Mathematics With Applications 59 Pp. 2615 – 2627.
  23. Ljung, L. (1987) "system Identification Theory For The User". Prentice-hall, Englewood Cliffs, Nj.
  24. Louhichi B. , Toumi A. , (2008) "identification Of Greenhouse Parameters Using Armax And Narmax Structures", International Review Of Physics (i. R. E. Phy. ) Vol. 2, N. 2, Pp. 129 – 138.
  25. Louhichi B. , Toumi A. , (2010) "identification Of Nonlinear Hammerstein – Wiener Armax Systems", 11th International Conference On Sciences And Techniques Of Automatic Control & Computer Engineering (sta'10), Monastir, Tunisie.
  26. Narendra, K. S. And Gallman, P. G. (1966) "an Iterative Method For The Identification Of Nonlinear Systems Using A Hammerstein Model". Ieee Transactions On Automatic Control, 11, Pp. 546 – 550.
  27. Pottmann, M. , Unbehauen, H. And Seborg, D. e. , (1993) "application Of General Multimodel Approach For Identification Of Highly Nonlinear Processes". Int J Control, 57 Pp. 97 – 120.
  28. Ramos J. a. , Durand J. f. , (1999) "identification Of Nonlinear Systems Using A B-splines Parametric Subspace Approach". Proceedings Of The American Control Conference, Vol. 6, Pp. 3955 – 3959.
  29. Sung S. w. , (2002) "system Identification Method For Hammerstein Processes". Industrial And Engineering Chemistry Research 41 (17) Pp. 4295 – 4302.
  30. Su, H. t. And Mcavoy, T. j. , (1993) "integration Of Multilayer Perception Networks And Linear Dynamic Models: A Hammerstein Modeling Approach". Ind Eng Chem Res, 26 Pp. 1927 – 1936.
  31. Wang, D. q. And Ding, F. , (2008) "extended Stochastic Gradient Identification Algorithms For Hammerstein – Wiener Armax Systems", Computers And Mathematics With Applications 56 Pp. 3157 – 3164.
  32. Zhu Y. , (2000) "identification Of Hammerstein Models For Control Using Asym", International Journal Of Control 73 (18) Pp. 1692 – 1702.
Index Terms

Computer Science
Information Sciences

Keywords

MIMO Hammerstein systems Parameter estimation Singular value decomposition method Recursive least squares algorithm Non linear systems

Powered by PhDFocusTM