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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Abstract

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.

Item Type:

Journal Article

Journal or Publication Title:

Electronics Letters

Additional Information:

©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Uncontrolled Keywords:

/dk/atira/pure/subjectarea/asjc/2200/2208

Subjects:

?? state space methodsstate estimationstate feedbackkalman filterslinear quadratic controlcontrolelectrical and electronic engineering ??

Departments:

Faculty of Science and Technology > Engineering

ID Code:

89312

Deposited By:

ep_importer_pure

Deposited On:

19 Dec 2017 16:48