This paper deals with a method for identification of nonlinear systems suitable to be described by Hammerstein models consisting of a static nonlinearity followed by an ARX linear model. The estimation of the static nonlinearity is carried out supplying the system with a sequence of step signals of various amplitude and determining the corresponding steady-state responses. The estimation of the parameters of the ARX linear system is carried out by means of a least square estimator using data generated supplying the system with a Pseudorandom Binary Sequence (PRBS). The method in question is able to identify static nonlinearities of general type, also with hysteresis and/or discontinuities. Simulation results confirm the validity of the method and its capabilities with respect to some other methods.
title = "Identification of Nonlinear Systems Described by Hammerstein Models",
abstract = "This paper deals with a method for identification of nonlinear systems suitable to be described by Hammerstein models consisting of a static nonlinearity followed by an ARX linear model. The estimation of the static nonlinearity is carried out supplying the system with a sequence of step signals of various amplitude and determining the corresponding steady-state responses. The estimation of the parameters of the ARX linear system is carried out by means of a least square estimator using data generated supplying the system with a Pseudorandom Binary Sequence (PRBS). The method in question is able to identify static nonlinearities of general type, also with hysteresis and/or discontinuities. Simulation results confirm the validity of the method and its capabilities with respect to some other methods.",
author = "Raimondi, {Francesco Maria} and Filippo D'Ippolito and Francesco Alonge and Salvatore Tumminaro",
year = "2004",
language = "English",
pages = "3990--3995",
}
TY - CONF
T1 - Identification of Nonlinear Systems Described by Hammerstein Models
AU - Raimondi, Francesco Maria
AU - D'Ippolito, Filippo
AU - Alonge, Francesco
AU - Tumminaro, Salvatore
PY - 2004
Y1 - 2004
N2 - This paper deals with a method for identification of nonlinear systems suitable to be described by Hammerstein models consisting of a static nonlinearity followed by an ARX linear model. The estimation of the static nonlinearity is carried out supplying the system with a sequence of step signals of various amplitude and determining the corresponding steady-state responses. The estimation of the parameters of the ARX linear system is carried out by means of a least square estimator using data generated supplying the system with a Pseudorandom Binary Sequence (PRBS). The method in question is able to identify static nonlinearities of general type, also with hysteresis and/or discontinuities. Simulation results confirm the validity of the method and its capabilities with respect to some other methods.
AB - This paper deals with a method for identification of nonlinear systems suitable to be described by Hammerstein models consisting of a static nonlinearity followed by an ARX linear model. The estimation of the static nonlinearity is carried out supplying the system with a sequence of step signals of various amplitude and determining the corresponding steady-state responses. The estimation of the parameters of the ARX linear system is carried out by means of a least square estimator using data generated supplying the system with a Pseudorandom Binary Sequence (PRBS). The method in question is able to identify static nonlinearities of general type, also with hysteresis and/or discontinuities. Simulation results confirm the validity of the method and its capabilities with respect to some other methods.