A new adaptive Kalman estimator integrated in a fault-tolerant control system

For sequential jumps detection, isolation and estimation in discrete-time stochastic linear systems, Willsky and Jones (1976) 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 test can be easily integrated in a Fault-Tolerant Control System (FTCS) via a control-law designed in order to asymptotically reject the effect of sequential jumps.