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Model-based detection of actuator faults in the presence of modelling errors

The problem of detecting actuator faults in the presence of modelling errors is addressed. A likelihood-ratio test is derived such that the effects of undermodelling are properly taken into account via a stochastic embedding technique. The resulting test takes form of the quadratic sum of prediction errors which has to be compared with a particular threshold value. Systematic choice of the threshold amounts to a demanding problem of approximating the distribution of the test statistics with normal distribution. The effectiveness of the test is demonstrated on a simulated motor-generator system.