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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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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Analysis and parameter estimation of nonlinear systems with Hammerstein model using Taylor series approach
Chung Hung-Yuan,Sun York-Yih +1 more
TL;DR: In this paper, the application of the Taylor series approach is considered for the analysis and estimation of the unknown parameters of nonlinear systems and direct and efficient computational algorithms, which are convenient and adaptable to digital programming, are developed.
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The shifted Legend re approach to non-linear system analysis and identification
Dong-Her Shih,Fan-Chu Kung +1 more
TL;DR: In this article, the shift-legendre polynomial expansion is applied to the analysis and identification of the non-linear system described by a Hammerstein model which consists of a single-valued nonlinearity followed by a linear plant.
Journal ArticleDOI
Convergence analysis for recursive Hammerstein identification
Per Mattsson,Torbjörn Wigren +1 more
TL;DR: This paper derives a recursive prediction error identification method based on the Hammerstein model structure that can only converge to stable stationary points of the associated ordinary differential equation.
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Identification of time-varying Hammerstein systems from ensemble data.
TL;DR: A new technique to identify rapidly time-varying Hammerstein systems from ensembles of input–output realizations is described and was found to produce excellent results under realistic conditions.
Journal ArticleDOI
Current Issues in Frequency Domain Experimentation
Robert G. Sargent,Tapas K. Som +1 more
TL;DR: In this paper, the authors present an examination of certain issues in Frequency Domain Experimentation FDE for discrete event simulation and conclude that conclusions drawn from FDE are dependent on the oscillation frequency and unless frequencies are chosen carefully, misleading results can be obtained.
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.
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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.