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Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener Models
Joint Authors
Source
Journal of Control Science and Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-06-06
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Electronic engineering
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Salhi, Houda& Kamoun, Samira. 2016. Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener Models. Journal of Control Science and Engineering،Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1107941
Modern Language Association (MLA)
Salhi, Houda& Kamoun, Samira. Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener Models. Journal of Control Science and Engineering No. 2016 (2016), pp.1-12.
https://search.emarefa.net/detail/BIM-1107941
American Medical Association (AMA)
Salhi, Houda& Kamoun, Samira. Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener Models. Journal of Control Science and Engineering. 2016. Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1107941
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1107941