Non-minimal state-space polynomial form of the Kalman filter for a general noise model
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EN
Article de revue
Ce document a été publié dans
Electronics Letters. 2018-02, vol. 54, n° 4, p. 204-206
Résumé en anglais
The optimal refined instrumental variable method for the estimation of the Box-Jenkins (BJ) model is modified so that it functions as an optimal filter and state-estimation algorithm. In contrast to the previously developed ...Lire la suite >
The optimal refined instrumental variable method for the estimation of the Box-Jenkins (BJ) model is modified so that it functions as an optimal filter and state-estimation algorithm. In contrast to the previously developed minimal and non-minimal state-space (NMSS) forms for an Auto-Regressive Moving Average with eXogenous variables (ARMAX) model, the new algorithm requires the introduction of a novel extended NMSS form. This facilitates representation of the more general noise component of the BJ model. The approach can be used for adaptive filtering and state variable feedback control.< Réduire
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SISTM
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