This paper presents the concept of fuzzy relational models for use in a fuzzy output estimator. A suitable "eld of application is in fault diagnosis, where output observation rather than state observation is needed for the generation of fault re#ecting residual signals. Due to their non-linear structure, fuzzy relational models can be used appropriately for building models of non-linear dynamic systems. In this paper, the identi"cation of fuzzy models for residual generation is discussed. Emphasis is placed upon the model-building procedure including the identi"cation 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.

This paper presents the concept of fuzzy relational models for use in a fuzzy output estimator. A suitable "eld of application is in fault diagnosis, where output observation rather than state observation is needed for the generation of fault re#ecting residual signals. Due to their non-linear structure, fuzzy relational models can be used appropriately for building models of non-linear dynamic systems. In this paper, the identi"cation of fuzzy models for residual generation is discussed. Emphasis is placed upon the model-building procedure including the identi"cation 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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