Model-based prognosis applied to a coupled four tank MIMO system
| Autor: | Pascal Vrignat, Manuel Avila, Frédéric Kratz, Toufik Aggab |
|---|---|
| Přispěvatelé: | Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et Energétique (PRISME), Université d'Orléans (UO)-Ecole Nationale Supérieure d'Ingénieurs de Bourges (ENSI Bourges), Avila, Manuel |
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
021103 operations research Observer (quantum physics) Computer science Maximum likelihood MIMO 0211 other engineering and technologies 02 engineering and technology [SPI.AUTO]Engineering Sciences [physics]/Automatic Nonlinear system [SPI.AUTO] Engineering Sciences [physics]/Automatic 020901 industrial engineering & automation Control and Systems Engineering Control theory Statistical inference Duration (project management) ComputingMilieux_MISCELLANEOUS |
| Zdroj: | IFAC-PapersOnLine. 51:655-661 |
| ISSN: | 2405-8963 |
| DOI: | 10.1016/j.ifacol.2018.09.645 |
| Popis: | In this paper, we propose a sensorless approach for failure prognosis. The approach deals with nonlinear Multiple-Input Multiple-Output system subject to degradations. The aim of this work was to estimate online the duration before the system performance requirement is no longer met, this without adding sensors. To carry out this aim, we used a Nonlinear Unknown Input Observer to estimate relevant parameters which are able to characterize system performance and a statistical inference method which is the maximum likelihood estimation to identify the models describing the parameter dynamics. To illustrate the performances of the approach, a simulated coupled four tank system was used. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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