A model-based approach to fault diagnosis in unmanned underwater vehicles

Actuator faults have been considered using an approximate model of the vehicle dynamics. Fault diagnosis is accomplished by means of a bank of estimators: a filter is implemented for each actuator's fault type, including the no-fault case. The estimators are extended Kalman filters due to the presence of nonlinearities in the dynamic models. Experimental results are reported to demonstrate the effectiveness of the proposed approach.