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

Lookup NU author(s): Dr Quentin Clairon

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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 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.

Publication metadata

Author(s): Wilson ED, Clairon Q, Taylor CJ

Publication type: Article

Publication status: Published

Journal: Electronics Letters

Year: 2018

Volume: 54

Issue: 4

Pages: 204-206

Online publication date: 27/02/2018

Acceptance date: 02/04/2016

ISSN (print): 0013-5194

ISSN (electronic): 1350-911X

Publisher: Institution of Engineering and Technology

URL: https://doi.org/10.1049/el.2017.3577

DOI: 10.1049/el.2017.3577

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