On the identification of Wiener systems with polynomial nonlinearity
| Autor: | Ricardo Castro-Garcia, Giulio Bottegai, Johan A. K. Suykens |
|---|---|
| Přispěvatelé: | Control Systems |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Polynomial Steady state (electronics) SISTA Linear system System identification 02 engineering and technology 01 natural sciences Least squares Nonlinear system Delta method 020901 industrial engineering & automation 0103 physical sciences DYSCO Applied mathematics Sine 010301 acoustics Mathematics |
| Zdroj: | 2017 IEEE 56th Annual Conference on Decision and Control (CDC) : December 12-15, 2017, Melbourne, Australia, 6475-6480 STARTPAGE=6475;ENDPAGE=6480;TITLE=2017 IEEE 56th Annual Conference on Decision and Control (CDC) : December 12-15, 2017, Melbourne, Australia CDC |
| Popis: | © 2017 IEEE. In this paper we introduce a new method for Wiener system identification that relies on the data collected on two separate experiments. In the first experiment, the system is excited with a sine signal at fixed frequency and phase shift. Using the steady state response of the system, we estimate the static nonlinearity, which is assumed to be a polynomial. In the second experiment, the system is fed with a persistently exciting input, which allows to identify the linear time-invariant block composing the Wiener structure. We show that the estimation of the static nonlinearity reduces to the solution of a least squares problem, and we provide an expression for the asymptotic variance of the estimated polynomial coefficients. The effectiveness of the method is demonstrated through numerical experiments. ispartof: pages:6475-6480 ispartof: Proc. of the 56th IEEE conference on Decision and Control vol:2018-January pages:6475-6480 ispartof: CDC 2017 location:Melbourne, Austrial date:12 Dec - 15 Dec 2017 status: published |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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