Quantification d'incertitudes d'un modèle à temps continu dans une procédure d'identification indirecte
| Autor: | Patrick Sibille |
|---|---|
| Přispěvatelé: | Centre de Recherche en Automatique de Nancy (CRAN), Université Henri Poincaré - Nancy 1 (UHP)-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Sibille, Patrick |
| Rok vydání: | 2010 |
| Předmět: |
identification indirecte
covariance des paramètres du modèle discret Covariance matrix Monte Carlo method Time constant Structure (category theory) Natural frequency Transfer function Industrial and Manufacturing Engineering [SPI.AUTO]Engineering Sciences [physics]/Automatic Computer Science Applications estimation de la matrice de covariance des paramètres Identification (information) [SPI.AUTO] Engineering Sciences [physics]/Automatic conversion modèle discret/modèle continu Control and Systems Engineering estimation d'incertitudes Damping factor région d'incertitude paramétrique Electrical and Electronic Engineering intervalle d'incertitude des paramètres Algorithm covariance des paramètres du modèle continu Mathematics |
| Zdroj: | Journal Européen des Systèmes Automatisés (JESA) Journal Européen des Systèmes Automatisés (JESA), Lavoisier, 2010, 44 (8), pp.913-939 |
| ISSN: | 1269-6935 |
| DOI: | 10.3166/jesa.44.913-939 |
| Popis: | This paper deals with the problem of indirect identification approach. In this framework, a new method for estimating the parameter covariance matrix (natural frequency, damping factor, static gain, time constant) of a continuous-time model is proposed. The indirect identification approach involves two steps: at first, a discrete-time model is obtained by applying discrete-time model estimation methods to the available sampled data; then, the discrete-time model is transformed into the required continuous-time model. The method proposed focuses on first and second orders transfer functions: uncertainties on static gain, time constants, natural frequency and damping factor are estimated directly, according to the model structure. Furthermore, this procedure is generalized to the case of transfer functions with an unspecified order. The resulting algorithm is then successfully applied to three examples via Monte Carlo simulations and numerical studies further illustrate the performances of the method. |
| Databáze: | OpenAIRE |
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