Identification for passive robust fault detection using zonotope-based set-membership approaches
In this paper, the problem of identification for passive robust fault detection, when a bounded description of the modelling uncertainty is considered, is addressed. Two set-membership identification methods are introduced to address this problem: the interval predictor and bounded error approaches....
| Autores: | , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2011 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/26646 |
| Acceso en línea: | https://hdl.handle.net/2117/26646 https://dx.doi.org/10.1002/acs.1242 |
| Access Level: | acceso abierto |
| Palabra clave: | Fault tolerance (Engineering) robust fault detection identification robust residuals zonotopes set-membership Tolerància als errors (Enginyeria) Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
| Sumario: | In this paper, the problem of identification for passive robust fault detection, when a bounded description of the modelling uncertainty is considered, is addressed. Two set-membership identification methods are introduced to address this problem: the interval predictor and bounded error approaches. These two identification approaches naturally lead to two robust fault detection tests: the direct and inverse tests, respectively, which are also introduced and discussed. Implementation algorithms make use of a zonotope to approximate the parameter uncertainty set. Moreover, underlying hypothesis of both approaches is discussed and applicability conditions are stated. A case study based on a four-tank system is used to illustrate the applicability and the properties of the two identification approaches as well as the corresponding fault detection |
|---|