Parameter identification for eigenstructure assignment in robust fault detection

The paper presents some results on parametric identification of linear systems applied to robust Fault Diagnosis schemes. In our approach, an equation error model is derived from input- output data. In particular, the error term takes into account disturbances (non measurable inputs), nonlinear and time-variant terms, measurement errors, etc. In this manner, state-space realization of the equation error model leads to define a disturbance distribution matrix related to the error term, and, thus, well-known eigenstructure assignment results for robust fault detection can be successfully applied. The proposed procedure has been tested on a industrial gas turbine prototype model in which a sensor fault is simulated. Results from this simulation campaign are also reported.