Journal ArticleDOI
An iterative method for the identification of nonlinear systems using a Hammerstein model
Kumpati S. Narendra,P. Gallman +1 more
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TLDR
In this article, an iterative method is proposed for the identification of nonlinear systems from samples of inputs and outputs in the presence of noise, which consists of a no-memory gain (of an assumed polynomial form) followed by a linear discrete system.Abstract:
An iterative method is proposed for the identification of nonlinear systems from samples of inputs and outputs in the presence of noise. The model used for the identification consists of a no-memory gain (of an assumed polynomial form) followed by a linear discrete system. The parameters of the pulse transfer function of the linear system and the coefficients of the polynomial non-linearity are alternately adjusted to minimize a mean square error criterion. Digital computer simulations are included to demonstrate the feasibility of the technique.read more
Citations
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Journal ArticleDOI
Kautz basis expansion-based Hammerstein system identification through separable least squares method
TL;DR: In this article, the authors proposed a novel Hammerstein system identification method based on the Kautz basis expansion and the separable least squares method, which can simultaneously estimate the linear and nonlinear parameters in a least squares framework.
Journal ArticleDOI
Hammerstein system identification with quantised inputs and quantised output observations
Jin Guo,Haitao Liu +1 more
TL;DR: In this article, a three-step algorithm is proposed to estimate the unknown parameters for the identifiable system and the strong convergence and the mean-square convergence rate of the algorithm are established, which can be achieved in terms of the Cramer-Rao lower bound by selecting a suitable transformation matrix.
Proceedings ArticleDOI
Blind Hammerstein Identification for MR Damper Modeling
TL;DR: A new blind approach to identification of Hammerstein systems, where a static nonlinearity precedes a linear dynamic system, is proposed by exploiting input's piece-wise constant property.
Journal ArticleDOI
On identification of block orientated systems by non-parametric techniques
Adam Krzyżak,Marian A. Partyka +1 more
TL;DR: An optimal model of a memoryless cascade system is derived and estimated by kernel regression and nonlinear dynamic systems of the Hammerstein and Wiener type are identified by means of non-parametric techniques.
Journal ArticleDOI
Closed-Loop Identification of Hammerstein Systems with Application to Gas Turbines
TL;DR: In this article, an iterative gradient-based method is proposed to simultaneously identify the nonlinear fuel valve characteristic and a low-order linear plant model in gas turbine applications that leverages a priori knowledge of both nonlinearity and engine dynamics.
References
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Journal ArticleDOI
A technique for the identification of linear systems
Kenneth Steiglitz,L. McBride +1 more
TL;DR: In this paper, an iterative technique is proposed to identify a linear system from samples of its input and output in the presence of noise by minimizing the mean-square error between system and model outputs.
Journal ArticleDOI
On the Identification Problem
TL;DR: In this paper, the identification of zero-memory multipoles and two-poles of class n_1 was studied, where the test signals are sine waves of different amplitudes and frequencies, and the measured quanity is the describing function of the device.