Non-minimal state space polynomial form of the Kalman filter for a general noise model

Wilson, Emma Denise and Clairon, Q. and Taylor, Charles James (2018) Non-minimal state space polynomial form of the Kalman filter for a general noise model. Electronics Letters, 54 (4). pp. 204-206. ISSN 0013-5194

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The optimal refined instrumental variable (RIV) 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.

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Journal Article
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Electronics Letters
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?? state space methodsstate estimationstate feedbackkalman filterslinear quadratic controlcontrolelectrical and electronic engineering ??
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19 Dec 2017 16:48
Last Modified:
25 Jun 2024 12:07