Diagnosis of parametric faults in multivariable nonlinear systems

This paper presents a new fault diagnosis scheme for parametric faults in nonlinear multivariable systems. It uses two consecutive observers, one for the state reconstruction and the second one as a reference model for the residual generation. Hence, the first one has to be robust against faults whereas the second one is sensitive to them. Faults are detected by calculating the moving norm of the difference between system output and reference model output. For fault isolation, this difference is compared to fault functions that are generated for given sets of faults. For this purpose, the moving angle serves as a measure of similarity. Moreover, small model uncertainties are considered. The theoretical results are confirmed by an simulation example.