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Identification de systèmes multivariables par modèle non entier en utilisant la méthode des sous-espaces

Abstract : The identification of systems by fractional models was initiated in the 1990s and various results have been obtained since. Nevertheless, most of these results are based on prediction error methods (PEM) of identification, based on the minimization of the norm of the estimation error. Apparent in 1996, the subspace methods are relatively new in the theory of the identification of linear systems. Based on geometric projections and linear algebra, they present an alternative to classical methods based on linear or nonlinear regression. They allow estimating the matrices of the state-space representation of a system. In the context of fractional systems, a pseudo-state-space representation generalizes the notion of state-space representation by introducing an additional parameter which is the commensurable order.Currently, the subspace method for non-integer systems has only been applied inthe time domain. It is then developed in this thesis for such a class of systems in the frequency domain. Moreover, since non-integer systems are continuous time systems, datapre-filtering is necessary to respect the causality of the signals and to be able to realize the identification. A study of the different filtering methods in the context of subspaceidentification is then carried out in order to deduce their advantages and disadvantages in the time domain. Finally, the method has been applied to a thermal diffusion system.The obtained models are generalized for several input heat flows, considering their temperature available at several measurement points.
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Submitted on : Monday, May 15, 2017 - 12:23:48 PM
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Elena Ivanova. Identification de systèmes multivariables par modèle non entier en utilisant la méthode des sous-espaces. Autre [cond-mat.other]. Université de Bordeaux, 2017. Français. ⟨NNT : 2017BORD0561⟩. ⟨tel-01522642⟩



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