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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

On the hermite series approach to nonparametric identification of hammerstein systems

TL;DR: In this paper, identification algorithms for a memoryless nonlinear part and for a linear dynamic part are proposed for nonlinear dynamic systems of Hammerstein type from input and output measurements.
Proceedings ArticleDOI

Estratégia avançada de sintonia para controle por matriz dinâmica com aplicação não-linear

TL;DR: In this paper, a metodo de sintonia automatica (autotuning) for o DMC com aplicacao em processos SISO that possam ser aproximados by um modelo FOPDT is presented.
Proceedings Article

On the use of L/sub 2/ gap metric for identifying Hammersteim models

TL;DR: In this paper, the authors consider the identification of nonlinear systems of the Hammerstein class and propose an iterative identification algorithm to obtain a model that minimizes the L/sub 2/ gap between the true and the identified model.
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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