Residual evaluation using time-frequency analysis for fault detection and isolation

The aim of the paper is to study the adaptive observer based fault detection and isolation with an emphasis on robustness to measurement noise. We develop a robust residual evaluation method based on time-frequency analysis. Our approach is tested in simulation on an alcoholic fermentation process. The faults are modelled as changes in the system parameters and residuals are generated using a set of adaptive observers.