Authors:
F. Lafont
1
;
N. Pessel
1
and
J. F. Balmat
2
Affiliations:
1
LSIS, UMR CNRS 6168, University of South-Toulon-Var, IUT of Toulon, France
;
2
LSIS, UMR CNRS 6168, University of South-Toulon-Var, Faculty of Sciences and Techniques, France
Keyword(s):
Adaptive model, fuzzy system models, diagnosis, Fault Detection and Isolation (FDI).
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Intelligent Fault Detection and Identification
Abstract:
This paper presents a new approach for the model-based diagnosis. The model is based on an adaptation with a variable forgetting factor. The variation of this factor is managed thanks to fuzzy logic. Thus, we propose a design method of a diagnosis system for the sensors defaults. In this study, the adaptive model is developed theoretically for the Multiple-Input Multiple-Output (MIMO) systems. We present the design stages of the fuzzy adaptive model and we give details of the Fault Detection and Isolation (FDI) principle. This approach is validated with a benchmark: a hydraulic process with three tanks. Different defaults (sensors) are simulated with the fuzzy adaptive model and the fuzzy approach for the diagnosis is compared with the residues method. The first results obtained are promising and seem applicable to a set of MIMO systems.