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An infinite-horizon robust filter for uncertain hidden Markov Models with conditional relative entropy constraints

Ford, Jason J., Ugrinovskii, Valery A., & Lai, John S. (2011) An infinite-horizon robust filter for uncertain hidden Markov Models with conditional relative entropy constraints. In Australian Control Conference, University of Melbourne, Melbourne, VIC. (In Press)

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    Abstract

    We consider a robust filtering problem for uncertain discrete-time, homogeneous, first-order, finite-state hidden Markov models (HMMs). The class of uncertain HMMs considered is described by a conditional relative entropy constraint on measures perturbed from a nominal regular conditional probability distribution given the previous posterior state distribution and the latest measurement. Under this class of perturbations, a robust infinite horizon filtering problem is first formulated as a constrained optimization problem before being transformed via variational results into an unconstrained optimization problem; the latter can be elegantly solved using a risk-sensitive information-state based filtering.

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    ID Code: 46498
    Item Type: Conference Paper
    Keywords: robust filtering, hidden Markov models (HMMs), conditional relative entropy
    Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100)
    Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)
    Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
    Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
    Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
    Past > Schools > School of Engineering Systems
    Copyright Owner: Copyright 2011 [please consult the authors]
    Deposited On: 17 Oct 2011 08:02
    Last Modified: 18 Oct 2011 06:30

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