Fault isolation in a class of nonlinear uncertain input-output systems

Xiaodong Zhang, Marios M. Polycarpou, Thomas Parisini

Abstract: Presents a robust fault isolation scheme for a class of nonlinear systems with unstructured modeling uncertainty and partial state measurement. The proposed fault diagnosis architecture consists of a fault detection and approximation estimator and a bank of isolation estimators. The isolation estimators are activated only if a fault is detected.. Based on the class of nonlinear systems under consideration, a fault isolability condition is rigorously investigated, characterizing the class of nonlinear faults which are isolable by the proposed scheme. Moreover, the non-conservativeness of the fault isolability condition is illustrated by deriving a subclass of nonlinear systems and faults for which this condition is also necessary for fault isolability.