Title
Least-squares-based iterative identification algorithm for Hammerstein nonlinear systems with non-uniform sampling
Abstract
This paper focuses on identification problems for Hammerstein systems with non-uniform sampling. By using the over-parameterization technique, we derive a linear regressive identification model with different input updating rates. To solve the identification problem of Hammerstein output error systems with the unmeasurable variables in the information vector, the least-squares-based iterative algorithm is presented by replacing the unmeasurable variables with their corresponding iterative estimates. The performances of the proposed algorithm are analysed and compared by using a numerical example.
Year
DOI
Venue
2013
10.1080/00207160.2012.758364
Int. J. Comput. Math.
Keywords
Field
DocType
hammerstein nonlinear system,corresponding iterative estimate,linear regressive identification model,unmeasurable variable,least-squares-based iterative identification algorithm,least-squares-based iterative algorithm,hammerstein system,non-uniform sampling,different input,information vector,proposed algorithm,identification problem,hammerstein output error system,least squares,parameter estimation,non uniform sampling,iterative algorithm
Least squares,Mathematical optimization,Nonlinear system,Iterative method,Hammerstein systems,Algorithm,Sampling (statistics),Estimation theory,Mathematics,Parameter identification problem,Nonuniform sampling
Journal
Volume
Issue
ISSN
90
7
0020-7160
Citations 
PageRank 
References 
9
0.52
36
Authors
3
Name
Order
Citations
PageRank
Xiangli Li1252.22
Ruifeng Ding226111.82
Lincheng Zhou3273.92