Proceedings ArticleDOI
A Contribution on the Identification of Nonlinear Systems
Adil Brouri,Laila Kadi +1 more
- pp 605-610
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TLDR
An identification method is proposed to determine the nonlinear systems parameters, which can be described by Wiener systems and involves easily generated excitation signals.Abstract:
In this paper, an identification method is proposed to determine the nonlinear systems parameters. The proposed nonlinear systems can be described by Wiener systems. This structure of models consists of series of linear dynamic element and a nonlinearity block. Both the linear and nonlinear parts are nonparametric. In particular, the linear subsystem of structure entirely unknown. The considered nonlinearity function is of hard type. This latter can have a dead zone or with preload. These nonlinear systems have been confirmed by several practical applications. The suggested approach involves easily generated excitation signals.read more
Citations
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Journal ArticleDOI
Identification of nonlinear systems having hard function
TL;DR: In this paper, an identification approach of nonlinear systems is studied, which can be described by Wiener-Hammerstein model, which is composed of a nonlinearity surrounded by two linear blocks.
Journal ArticleDOI
Parameter Identification of Switched Reluctance Motor Using Exponential Swept-Sine Signal
Abdelmalek Ouannou,Adil Brouri,Fouad Giri,Laila Kadi,H. Oubouaddi,Shimaa A. Hussien,Norah Alwadai,Mohamed I. Mosaad +7 more
TL;DR: In this article , a generalized polynomial Hammerstein model is proposed for modeling SRM parameters, and an identification method is proposed to obtain estimates of SRM parameter parameters by exciting the system with a swept-sine signal.
Journal ArticleDOI
Identification of Nonparametric Nonlinear Systems
Mohamed Benyassi,Adil Brouri +1 more
TL;DR: In this paper, a nonlinear system is described by Hammerstein models and the determination of linear and nonlinear block can be done using a unique stage, where the linear subsystem is not necessarily parametric and the nonlinear function can be nonparametric smooth nonlinearity.
Journal ArticleDOI
Spectral Determination of Nonlinear System Parameters
Adil Brouri,Mohamed Benyassi +1 more
TL;DR: In this paper, an identification method of nonlinear system is proposed, where the system nonlinearity is allowed to be noninvertible general shape nonlinearness but it must be approximated by a polynomial function.
References
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Journal ArticleDOI
Nonlinear System Identification
TL;DR: This is a comprehensive book discussing several methods for the identification of nonlinear systems, ranging from linear optimization techniques to fuzzy logic and nonlinear adaptive control, and Nelles has certainly described an extensive number of results.
Journal ArticleDOI
Recursive prediction error identification using the nonlinear Wiener model
TL;DR: A recursive prediction error identification algorithm, based on the Wiener model, is derived and shows that the input signal should be such that there is signal energy in the whole range of the piecewise linear approximation.
Journal ArticleDOI
Identifying MIMO Wiener systems using subspace model identification methods
TL;DR: It is shown that the MOESP (Multivariable Output-Error State sPace) class of subspace model identification schemes can be extended to identify Wiener systems, a series connection of a linear dynamic system followed by a static nonlinearity.
Journal ArticleDOI
Recursive subspace identification of linear and non-linear Wiener state-space models
TL;DR: The MOESP class of identification algorithms are made recursive on the basis of various updating schemes for subspace tracking.
Journal ArticleDOI
Convergence analysis of recursive identification algorithms based on the nonlinear Wiener model
TL;DR: It is proved that global convergence of the schemes is tied to sector conditions on the static nonlinearity of FIR (finite impulse response) models, and Gauss-Newton and stochastic gradient algorithms are suggested in the single-input/single-output case.