Non-minimal state-space polynomial form of the Kalman filter for a general noise model
Language
EN
Article de revue
This item was published in
Electronics Letters. 2018-02, vol. 54, n° 4, p. 204-206
English Abstract
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 ...Read more >
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.Read less <
English Keywords
SISTM