Unknown-input observability with an application to prognostics for Waste Water Treatment Plants
| Autor: | Jean-François Balmat, Frédéric Lafont, Nathalie Pessel, Jean-Paul Gauthier |
|---|---|
| Přispěvatelé: | Laboratoire des Sciences de l'Information et des Systèmes (LSIS), Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Université de Toulon (UTLN)-Aix Marseille Université (AMU), Geometric Control Design (GECO), Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS) |
| Rok vydání: | 2014 |
| Předmět: |
Engineering
Schedule Waste management business.industry General Engineering Process (computing) Observable 6. Clean water [SPI.AUTO]Engineering Sciences [physics]/Automatic Control theory Waste water treatment plant Prognostics Standard observer Observability business ComputingMilieux_MISCELLANEOUS Degradation (telecommunications) |
| Zdroj: | European Journal of Control European Journal of Control, Elsevier, 2014, 20 (2), pp.9. ⟨10.1016/j.ejcon.2014.01.002⟩ European Journal of Control, 2014, 20 (2), pp.9. ⟨10.1016/j.ejcon.2014.01.002⟩ |
| ISSN: | 0947-3580 |
| DOI: | 10.1016/j.ejcon.2014.01.002 |
| Popis: | This paper is devoted to the problem of model-based prognostics for a Waste Water Treatment Plant (WWTP). Our aim is to predict degradation of certain parameters in the process, in order to anticipate malfunctions and to schedule maintenance. It turns out that a WWTP, together with the possible malfunction, has a specific structure: mostly, the malfunction appears in the model as an unknown input function. The process is observable whatever this unknown input is, and the unknown input can itself be identified through the observations. Due to this property, our method does not require any assumption of the type “slow dynamics degradation”, as is usually assumed in ordinary prognostic methods. Our system being unknown-input observable, standard observer-based methods are enough to solve prognostic problems. Simulation results are shown for a typical WWTP. |
| Databáze: | OpenAIRE |
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