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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

Piecewise Global Volterra Nonlinear Modeling and Characterization for Aircraft Dynamics

TL;DR: In this article, a piecewise Volterra kernel approach was proposed to evaluate global aircraft dynamic behavior by using sub-model VOLTERRA kernels to build global kernels, which was compared with a global linear approach while employing the nonlinear simulation as the benchmark.
Journal ArticleDOI

Recursive nonparametric identification of Hammerstein systems

TL;DR: Two new algorithms of a recursive form for estimating the nonlinear characteristic of the Hammerstein system converge at all continuity points of the characteristic, and the integrated absolute error converges to zero.
Journal ArticleDOI

Improving distribution system stability by predictive control of gas turbines

TL;DR: In this paper, model predictive control (MPC) is used to damp the oscillation when the power distribution system is subjected to a disturbance, which can explicitly handle the nonlinearities and constraints of many variables in a single control formulation.
Patent

Conversion of a PCM signal into a UPWM signal

TL;DR: In this article, a model is made of the known non-linearity in the conversion by dividing a plurality of nonlinearity components in the model, where the polynomial components are separately weighted with filter coefficients.
Journal ArticleDOI

System identification using Hammerstein model optimized with differential evolution algorithm

TL;DR: In this article, a Hammerstein model is presented which is obtained by cascade form of a nonlinear second order volterra (SOV) and a linear FIR model, which is optimized with differential evolution algorithm (DEA).
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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