NDLI: Identification of continuous-time Hammerstein models using Simultaneous Perturbation Stochastic Approximation

Content Provider	IEEE Xplore Digital Library
Author	Ahmad, M.A. Azuma, S.-I. Sugie, T.
Copyright Year	2014
Description	Author affiliation: Dept. of Syst. Sci., Kyoto Univ., Kyoto, Japan (Ahmad, M.A.; Azuma, S.-I.; Sugie, T.)
Abstract	This paper performs an initial study on identification of continuous-time Hammerstein models based on Simultaneous Perturbation Stochastic Approximation (SPSA). While the structure information such as the system order is available for the linear subsystems, the structure of nonlinear subsystem is assumed to be completely unknown. For handling it, a piecewise-linear functions are used as a tool to approximate the unknown nonlinear functions. The SPSA based method is then used to estimate the parameters in both the linear and nonlinear parts based on the given input and output data. A numerical example is given to illustrate that the SPSA based algorithm can give an accurate parameter estimation of the Hammerstein models with high probability through detailed simulation.
Starting Page	1107
Ending Page	1111
File Size	633451
Page Count	5
File Format	PDF
ISSN	20937121
e-ISBN	9788993215076
DOI	10.1109/ICCAS.2014.6987545
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-22
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Control, Robotics and Systems (ICROS)
Subject Keyword	nonlinear system identification Hammerstein model stochastic approximation Approximation methods
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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