A generalized likelihood ratio test for a fault-tolerant control system

Willsky and Jones (1976) have developed the generalized likelihood ratio (GLR) test for sequential jumps detection, isolation and estimation in discrete time stochastic linear systems. 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. With this updating strategy, the rate of good decisions is not guaranteed to be maximized. To solve this problem, the proposed active GLR test will be based on a reference model updated on line after each detection and isolation of one jump. To reduce the computational requirement, the passive GLR test will be derived from a state estimator designed on a fixed reference model directly sensitive to system changes. We will show that the active and passive GLR tests can be easily integrated in a reconfigurable fault tolerant control system (FTCS) to asymptotically recover the nominal system performances of the jump free system.