Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener Models
This paper deals with the parameter estimation problem for multivariable nonlinear systems described by MIMO state-space Wiener models. Recursive parameters and state estimation algorithms are presented using the least squares technique, the adjustable model, and the Kalman filter theory. The basic...
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Format: | Article |
Language: | English |
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Wiley
2016-01-01
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Series: | Journal of Control Science and Engineering |
Online Access: | http://dx.doi.org/10.1155/2016/9614167 |
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author | Houda Salhi Samira Kamoun |
author_facet | Houda Salhi Samira Kamoun |
author_sort | Houda Salhi |
collection | DOAJ |
description | This paper deals with the parameter estimation problem for multivariable nonlinear systems described by MIMO state-space Wiener models. Recursive parameters and state estimation algorithms are presented using the least squares technique, the adjustable model, and the Kalman filter theory. The basic idea is to estimate jointly the parameters, the state vector, and the internal variables of MIMO Wiener models based on a specific decomposition technique to extract the internal vector and avoid problems related to invertibility assumption. The effectiveness of the proposed algorithms is shown by an illustrative simulation example. |
format | Article |
id | doaj-art-4f876834454347fe878eaadef5ba9504 |
institution | Kabale University |
issn | 1687-5249 1687-5257 |
language | English |
publishDate | 2016-01-01 |
publisher | Wiley |
record_format | Article |
series | Journal of Control Science and Engineering |
spelling | doaj-art-4f876834454347fe878eaadef5ba95042025-02-03T06:13:10ZengWileyJournal of Control Science and Engineering1687-52491687-52572016-01-01201610.1155/2016/96141679614167Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener ModelsHouda Salhi0Samira Kamoun1University of Sfax, National Engineering School of Sfax (ENIS), Laboratory of Sciences and Technique of Automatic Control and Computer Engineering (Lab-SAT), BP 1173, 3038 Sfax, TunisiaUniversity of Sfax, National Engineering School of Sfax (ENIS), Laboratory of Sciences and Technique of Automatic Control and Computer Engineering (Lab-SAT), BP 1173, 3038 Sfax, TunisiaThis paper deals with the parameter estimation problem for multivariable nonlinear systems described by MIMO state-space Wiener models. Recursive parameters and state estimation algorithms are presented using the least squares technique, the adjustable model, and the Kalman filter theory. The basic idea is to estimate jointly the parameters, the state vector, and the internal variables of MIMO Wiener models based on a specific decomposition technique to extract the internal vector and avoid problems related to invertibility assumption. The effectiveness of the proposed algorithms is shown by an illustrative simulation example.http://dx.doi.org/10.1155/2016/9614167 |
spellingShingle | Houda Salhi Samira Kamoun Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener Models Journal of Control Science and Engineering |
title | Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener Models |
title_full | Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener Models |
title_fullStr | Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener Models |
title_full_unstemmed | Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener Models |
title_short | Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener Models |
title_sort | combined parameter and state estimation algorithms for multivariable nonlinear systems using mimo wiener models |
url | http://dx.doi.org/10.1155/2016/9614167 |
work_keys_str_mv | AT houdasalhi combinedparameterandstateestimationalgorithmsformultivariablenonlinearsystemsusingmimowienermodels AT samirakamoun combinedparameterandstateestimationalgorithmsformultivariablenonlinearsystemsusingmimowienermodels |