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Journal ArticleDOI

An iterative method for the identification of nonlinear systems using a Hammerstein model

Kumpati S. Narendra, +1 more
- 01 Jul 1966 - 
- Vol. 11, Iss: 3, pp 546-550
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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.

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Citations
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Journal ArticleDOI

Valve Stiction Model Estimation in Closed-loop Operation

TL;DR: By parameterizing the valve stiction model as a form of cubic splines, an identification method is proposed using a relaxation iteration scheme and the consistency of the method is established.
Proceedings ArticleDOI

Gray-box models via approximate steady-state matching

TL;DR: The extent of steady-state variability, the consequences of that variability on gray-box identification results, and some ideas for dealing with this variability based on the notions of set-theoretic parameter estimation are considered.
Journal ArticleDOI

A Design Method for Multi-Input Single-Output Nonlinear Adaptive Digital Filters Using Neural Networks

TL;DR: This paper presents a design method for multi-input single-outputt nonlinear adaptive digital filters using neural networks using back-propagation training of par allel connected several small-scale feedforward multilayered neural networks to design the non linear adaptive digital filter required for real time processing with many parameters.
Proceedings ArticleDOI

Identification of hammerstein systems by the hermite series estimate with application to flexible robot manipulators control

TL;DR: In this paper, a single-input, single-output discrete Hammerstein system with two cascaded subsystems, a nonlinear, memoryless subsystem followed by a dynamic, linear subsystem, is identified by the correlation and Newton-Gauss method.
References
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Journal ArticleDOI

A technique for the identification of linear systems

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.
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