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
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Proceedings ArticleDOI
A two-stage parameter bounding procedure for Hammerstein models with bounded output errors
Vito Cerone,Diego Regruto +1 more
TL;DR: A two-stage procedure for deriving parameters bounds in Hammerstein models when the output measurement errors are bounded and tight bounds on the unmeasurable inner signal together with noisy output measurements are used for bounding the parameters of the linear dynamic block.
Journal ArticleDOI
Feedforward Control in the Presence of Input Nonlinearities: A Learning-based Approach
TL;DR: In this paper , a data-driven feed-forward controller was developed to address input nonlinearities, which are common in typical applications such as semiconductor back-end equipment.
Proceedings ArticleDOI
Identification of ARX Hammerstein Models based on Twin Support Vector Machine Regression
TL;DR: A new algorithm to identify Auto-Regressive Exogenous (ARX) input Hammerstein Models based on Twin Support Vector Machine Regression (TSVR) by minimizing two ε-insensitive loss functions is developed.
Self-tuning control of bilinear systems
M. Farsi,A. Abdulaziz +1 more
TL;DR: In this article, the authors deal with self-tuning control of Hammerstein type bi-linear systems that contain linear parameters and a nonlinear quasi-input function of the real input signal.
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.