Refined IV-based method for LPV partial differential equation model identification
| Autor: | Julien Schorsch, Marion Gilson, Vincent Laurain, Hugues Garnier |
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| Přispěvatelé: | Centre de Recherche en Automatique de Nancy (CRAN), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Schorsch, Julien |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Partial differential equation
First-order partial differential equation System identification Distributed-Parameter Systems Convolution Stochastic partial differential equation Instrumental variable Control theory Distributed parameter system Product (mathematics) partial differential equation [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering Applied mathematics [INFO.INFO-AU] Computer Science [cs]/Automatic Control Engineering Numerical partial differential equations Mathematics |
| Zdroj: | 13th European Control Conference, ECC'14 13th European Control Conference, ECC'14, Jun 2014, Strasbourg, France. pp.2127-2132 ECC HAL Publons |
| Popis: | International audience; This paper presents a direct identification method for linear parameter varying models described by partial differential equations in an input-output setting. The continuous space-time model is firstly rewritten as a multiple-input singleoutput model. The continuous filtering operations are reformulated as a discrete convolution product and a refined instrumental variable technique is developed to efficiently estimate the model parameters. The performance of the proposed method is then illustrated via a representative simulation example. |
| Databáze: | OpenAIRE |
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