A fuzzy parametric approach for the model-based diagnosis

被引：0

作者：

Lafont, F. ^{[1
]}

Pessel, N. ^{[1
]}

Balmat, J. F. ^{[2
]}

机构：

[1] Univ S Toulon Var, CNRS UMR 6168, LSIS, IUT Toulon, BP 20132, F-83957 La Garde, France

[2] Univ S Toulon Var, CNRS UMR 6168, LSIS, Fac Tech Sci, F-83957 La Garde, France

来源：

ICINCO 2007: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL ICSO: INTELLIGENT CONTROL SYSTEMS AND OPTIMIZATION | 2007年

关键词：

adaptive model; fuzzy system models; diagnosis; Fault Detection and Isolation (FDI);

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：25 / +

页数：2

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