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.
Identification of fuzzy relational models for fault detection
Identifikation von Fuzzy-Relationsmodellen für die Fehlererkennung
Control Engineering Practice ; 9 , 5 ; 555-562
2001
8 Seiten, 13 Bilder, 12 Quellen
Article (Journal)
English
Fault Identification Method Based on Fuzzy Fault Petri Net
British Library Conference Proceedings | 2016
|Dynamic Fuzzy Models of the Fastrac Startup Sequence for Fault Detection
British Library Conference Proceedings | 2008
|Unsupervised multivariate relational fault detection system for a vehicle and method therefor
European Patent Office | 2020
|