Least-Squares Parameter Estimation Algorithm for a Class of Input Nonlinear Systems
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-08-13
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
This paper studies least-squares parameter estimation algorithms for input nonlinear systems, including the input nonlinear controlled autoregressive (IN-CAR) model and the input nonlinear controlled autoregressive autoregressive moving average (IN-CARARMA) model.
The basic idea is to obtain linear-in-parameters models by overparameterizing such nonlinear systems and to use the least-squares algorithm to estimate the unknown parameter vectors.
It is proved that the parameter estimates consistently converge to their true values under the persistent excitation condition.
A simulation example is provided.
American Psychological Association (APA)
Xiong, Weili& Fan, Wei& Ding, Rui. 2012. Least-Squares Parameter Estimation Algorithm for a Class of Input Nonlinear Systems. Journal of Applied Mathematics،Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-1028970
Modern Language Association (MLA)
Xiong, Weili…[et al.]. Least-Squares Parameter Estimation Algorithm for a Class of Input Nonlinear Systems. Journal of Applied Mathematics No. 2012 (2012), pp.1-14.
https://search.emarefa.net/detail/BIM-1028970
American Medical Association (AMA)
Xiong, Weili& Fan, Wei& Ding, Rui. Least-Squares Parameter Estimation Algorithm for a Class of Input Nonlinear Systems. Journal of Applied Mathematics. 2012. Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-1028970
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1028970