Optimal control: linear quadratic methods
Optimal control: linear quadratic methods
Detection of abrupt changes: theory and application
Detection of abrupt changes: theory and application
Robust model-based fault diagnosis for dynamic systems
Robust model-based fault diagnosis for dynamic systems
Technical Communique: Fault isolation filter design for linear stochastic systems
Automatica (Journal of IFAC)
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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.