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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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.read more
Citations
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Nonlinear Multivariable Predictive Controls with Laguerre-based Wiener Neural Network Models and Partial Least Squares Model Reduction
TL;DR: Pelkola et al. as mentioned in this paper used Laguerre-based Wiener Neural Network models and Partial Least Squares (PLS) model structure for dynamic modeling and control of nonlinear multivariable systems.
Dissertation
Identification et modélisation de systèmes non linéaires générant des sous et ultra-harmoniques : application à l'imagerie ultrasonore sous et ultra-harmonique
TL;DR: Dans les annees 2000, une methode permettant la modelisation de sous et ultra-harmoniques en utilisant un modele de Volterra a plusieurs entrees (Muliple Input Single Output : MISO) a ete developpee.
Proceedings ArticleDOI
Evaluation of estimated hammerstein models via normalized projection misalignment of linear and nonlinear subsystems
TL;DR: Irrespective of particular identification algorithms, this paper generalizes the framework of parameter-and output-based performance metrics known from linear systems and resolves an ambiguity in system parameters via the projection misalignment technique.
Proceedings ArticleDOI
Conditional center computation in the identification of approximated Hammerstein models
Laura Giarre,Giovanni Zappa +1 more
TL;DR: A new approach is proposed in which the identification of a low complexity Hammerstein model amounts to the computation of the Chebychev center of a set of matrices conditioned to the manifold of rank-one matrices.
Proceedings ArticleDOI
Prediction based Control Strategy in Industrial Applications - A Review
TL;DR: This paper provides a rigorous review of the evolution pertaining to linear MPC and its variants and highlights MPC strategy and its implementation for design of MPC basedcontroller.
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.
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.