Filter-Based Fault Detection and Isolation in Distributed Parameter Systems Modeled by Parabolic Partial Differential Equations

This paper covers model-based fault detection and isolation for linear nonlinear distributed parameter systems (DPS). The first part mainly deals with actuator, sensor state a class of DPS represented by set coupled partial differential equations (PDE). A filter based observer is designed on the PDE representation using which residual generated. detected when magnitude exceeds threshold. Upon detection, several estimators are filters whose output residuals compared predefined thresholds. declared to be certain type if corresponding estimator below its threshold while other above Next, location determined identified. second this focuses Luenberger observer. Here framework introduced isolate faults isolability condition additional boundary measurements without filters. Finally, effectiveness proposed schemes both demonstrated through simulation.