This paper presents the concept of fuzzy relational models for use in a fuzzy output estimator. A suitable field of application is in fault diagnosis, where output observation rather than state observation is needed for the generation of fault reflecting residual signals. Due to their non-linear structure, fuzzy relational models can be used appropriately for building models of non-linear dynamic systerns. In this paper, the identification of fuzzy models for residual generation is discussed. Emphasis is placed upon the model-building procedure including the identification of the model structure and of the parameters. As an application example, a real technical system is considered. The case study presents the detection of oversteering of a passenger car. The results of the application to residual generation are discussed.


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    Title :

    Identification of fuzzy relational models for fault detection


    Additional title:

    Identifikation von Fuzzy-Relationsmodellen für die Fehlererkennung


    Contributors:
    Amann, P. (author) / Perronne, H.M. (author) / Gissinger, G.L. (author) / Frank, P.M. (author)

    Published in:

    Publication date :

    2001


    Size :

    8 Seiten, 13 Bilder, 12 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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