Fault Diagnosis Using Set-Membership Approaches

As discussed in Chap. 4, model-based fault detection of dynamic processes is based on the use of models (i.e., analytical redundancy) to check the consistency of observed behaviours. However, when building a model of a dynamic process to monitor its behaviour, there is always some mismatch between the modelled and real behaviour due to the fact that some effects are neglected, some non-linearities are linearised in order to simplify the model, some parameters have tolerance when are compared between several units of the same component, some errors in parameters (or in the structure) of the model are introduced in the model identification process, etc. These modelling errors introduce some uncertainty in the model.

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