DocumentCode
3165305
Title
Parameter Identification for Input Nonlinear Output-Error Systems Using the Unknown Variable Estimation
Author
Shi, Yang ; Ding, Feng
fYear
2007
fDate
9-13 July 2007
Firstpage
118
Lastpage
121
Abstract
The information vector in the identification model obtained by parameterizing input nonlinear systems contains unknown variables - the noise-free (true) outputs of the system. This is the difficulty of identification. This paper develops a stochastic gradient based identification algorithm by replacing the unknown variable with its estimate. The simulation results show the effectiveness of the proposed algorithms.
Keywords
gradient methods; nonlinear systems; parameter estimation; stochastic processes; input nonlinear output-error systems; noise-free outputs; parameter identification; stochastic gradient based identification; unknown variable estimation; Additive noise; Algorithm design and analysis; Convergence; Iterative algorithms; Iterative methods; Nonlinear control systems; Nonlinear systems; Parameter estimation; Stochastic resonance; Symmetric matrices;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2007. ACC '07
Conference_Location
New York, NY
ISSN
0743-1619
Print_ISBN
1-4244-0988-8
Electronic_ISBN
0743-1619
Type
conf
DOI
10.1109/ACC.2007.4282542
Filename
4282542
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