Fault diagnosis for LTI systems based on system identification

A new fault diagnosis strategy based on system identification is proposed. The underlying faults, mainly sensor bias and actuator additive bias, are parameterized in the model which is estimated in two stages. In the first stage, the contribution of the fault is estimated. In the second stage, the faults are recovered from the residual. For the component faults, we use online parameter identification to monitor the fault. Recursive online monitoring algorithms are derived. Examples are given to illustrate the effectiveness of the proposed method.