A new adaptive Kalman estimator for detection and isolation of multiples faults using modified GLR test

For sequential jumps detection, isolation and estimation in discrete-time stochastic linear systems, Willsky and Jones. have developed the Generalized Likelihood Ratio (GLR) test. After each detection and isolation of one jump, the treatment of another possible jump is obtained by a direct state estimate and covariance incrementation of the Kalman filter originally designed on the jump-free system. This paper proposes to extend this approach from a state estimator designed on a reference model directly sensitive to system changes. We will show that the obtained passive GLR gives good results with compared to Willsky methods.