Unbiased minimum-variance linear state estimation
Automatica (Journal of IFAC)
Innovations generation in the presence of unknown inputs: application to robust failure detection
Automatica (Journal of IFAC)
Unbiased minimum variance estimation for systems with unknown exogenous inputs
Automatica (Journal of IFAC)
Robust model-based fault diagnosis for dynamic systems
Robust model-based fault diagnosis for dynamic systems
Diagnosis and Fault-Tolerant Control
Diagnosis and Fault-Tolerant Control
Brief paper: Unbiased minimum-variance input and state estimation for linear discrete-time systems
Automatica (Journal of IFAC)
Brief paper: Unbiased minimum-variance state estimation for linear systems with unknown input
Automatica (Journal of IFAC)
Technical Communique: Fault isolation filter design for linear stochastic systems
Automatica (Journal of IFAC)
Brief Extension of minimum variance estimation for systems with unknown inputs
Automatica (Journal of IFAC)
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This paper studies recursive optimal filtering as well as robust fault and state estimation for linear stochastic systems with unknown disturbances. It proposes a new recursive optimal filter structure with transformation of the original system. This transformation is based on the singular value decomposition of the direct feedthrough matrix distribution of the fault which is assumed to be of arbitrary rank. The resulting filter is optimal in the sense of the unbiased minimum-variance criteria. Two numerical examples are given in order to illustrate the proposed method, in particular to solve the estimation of the simultaneous actuator and sensor fault problem and to make a comparison with the existing literature results.