Relative entropy rate based model selection for linear hybrid system filters of uncertain nonlinear systems

Techakesari, Onvaree & Ford, Jason J. (2013) Relative entropy rate based model selection for linear hybrid system filters of uncertain nonlinear systems. Signal Processing, 93(1), pp. 12-22.

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Hybrid system representations have been exploited in a number of challenging modelling situations, including situations where the original nonlinear dynamics are too complex (or too imprecisely known) to be directly filtered. Unfortunately, the question of how to best design suitable hybrid system models has not yet been fully addressed, particularly in the situations involving model uncertainty. This paper proposes a novel joint state-measurement relative entropy rate based approach for design of hybrid system filters in the presence of (parameterised) model uncertainty. We also present a design approach suitable for suboptimal hybrid system filters. The benefits of our proposed approaches are illustrated through design examples and simulation studies.

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ID Code: 51514
Item Type: Journal Article
Refereed: Yes
Keywords: Hybrid system model, Model selection, Approximate filtering, Relative entropy rate
DOI: 10.1016/j.sigpro.2012.05.028
ISSN: 0165-1684
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright Elsevier BV
Copyright Statement: “NOTICE: this is the author’s version of a work that was accepted for publication in Signal Processing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Signal Processing, [VOL:93, ISSUE:1, (2013)] DOI10.1016/j.sigpro.2012.05.028”
Deposited On: 10 Jul 2012 03:15
Last Modified: 15 Sep 2014 03:20

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