Modelling for fault detection and isolation versus modelling for control

The goal of this paper is to emphasize both the particularities of models needed for model-based fault detection and isolation (FDI) and the differences with respect to the models used in control. Of special interest is the question of complexity. This depends basically on the given situation such as the kind of plant, the kind and number of faults to be detected, the demands for fault isolation, robustness and the measurements available. However, in contrast to the wide-spread opinion that models for FDI have always to be more complex than those for control, the paper shows that diagnostic models for controllable and observable plants comprise only a partial description of the input/output model and are therefore less complex than those for control. This issue is discussed in terms of different model-based FDI approaches — analytical, data- and knowledge-based. As for the analytical approaches the necessary order of the diagnostic model is that of the transfer operator from the fault vector to the system output.