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Structure Adaptation of Nonlinear Filters based on Non-Gaussianity Measures

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F15%3A43925644" target="_blank" >RIV/49777513:23520/15:43925644 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/ACC.2015.7171819" target="_blank" >http://dx.doi.org/10.1109/ACC.2015.7171819</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ACC.2015.7171819" target="_blank" >10.1109/ACC.2015.7171819</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Structure Adaptation of Nonlinear Filters based on Non-Gaussianity Measures

  • Original language description

    The paper deals with state estimation of stochastic nonlinear dynamical systems. A structure adaptation of nonlinear filters is proposed to reduce errors stemming from approximations made by the filters. The adaptation is controlled by non-Gaussian measures which assess current working conditions of the filter. A large non-Gaussian measure indicates a possible large approximation error and results in splitting the state conditional probability density function. To limit computational complexity of the filter given by the number of terms, a reduction of this number is done by merging some terms. The algorithm of the proposed filter with structure adaptation is detailed using the extended Kalman filter relations. Performance of the filter is illustrated in a numerical example.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

    <a href="/en/project/GA15-12068S" target="_blank" >GA15-12068S: Adaptive Approaches to State Estimation of Nonlinear Stochastic Systems</a><br>

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 2015 American Control Conference

  • ISBN

    978-1-4799-8684-2

  • ISSN

    0743-1619

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    3162-3167

  • Publisher name

    IEEE

  • Place of publication

    Chicago

  • Event location

    Chicago, USA

  • Event date

    Jul 1, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000370259203042