DocumentCode
581836
Title
Auxiliary model based recursive extended least squares and maximum likelihood estimation algorithms for input nonlinear systems
Author
Junhong, Li ; Ping, Jiang ; Hairong, Zhu ; Rui, Ding
fYear
2012
fDate
25-27 July 2012
Firstpage
1848
Lastpage
1853
Abstract
This paper studies the identification problems of input nonlinear controlled autoregressive moving average (IN-CARMA) systems, and derived an auxiliary model based recursive extended least squares (AM-RELS) algorithm and a maximum likelihood algorithm based on the Newton optimization method. The simulation results show that the proposed algorithm are effective.
Keywords
Newton method; least squares approximations; maximum likelihood estimation; nonlinear control systems; optimisation; AM-RELS; IN-CARMA; Newton optimization method; auxiliary model based recursive extended least squares; input nonlinear controlled autoregressive moving average; maximum likelihood estimation algorithms; Autoregressive processes; Computational modeling; Mathematical model; Maximum likelihood estimation; Nonlinear systems; Signal processing algorithms; Stochastic processes; Hammerstein model; Least squares; Maximum likelihood estimation; Newton method; Recursive identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2012 31st Chinese
Conference_Location
Hefei
ISSN
1934-1768
Print_ISBN
978-1-4673-2581-3
Type
conf
Filename
6390225
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