Unbiased minimum-variance linear state estimation
Automatica (Journal of IFAC)
Fault diagnosis in dynamic systems: theory and application
Fault diagnosis in dynamic systems: theory and application
Unbiased minimum variance estimation for systems with unknown exogenous inputs
Automatica (Journal of IFAC)
Speed and rotor flux estimation of induction machines using a two-stage extended Kalman filter
Automatica (Journal of IFAC)
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This paper presents a two-stage estimator for bias and state filtering in discrete-time stochastic linear systems affected by unknown inputs or disturbances. We show that the state estimate can be expressed as X"k"/"k=X@?"k"/"k+@b"k"/"kb"k"/"k where X@?"k"/"k is a bias-free state estimate and b"k"/"k the optimal estimate of constant bias. The proposed two-stage estimator is based on an alternate derivation of the unbiased minimum variance estimator with unknown exogenous inputs developed by Darouach and Zasadzinski (1997, Automatica 33, 717-719).