Parameter Estimation in Linear Dynamic Systems using Bayesian networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24210%2F19%3A00006706" target="_blank" >RIV/46747885:24210/19:00006706 - isvavai.cz</a>
Alternative codes found
RIV/46747885:24220/19:00006706
Result on the web
<a href="https://ieeexplore.ieee.org/document/8815029" target="_blank" >https://ieeexplore.ieee.org/document/8815029</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/PC.2019.8815029" target="_blank" >10.1109/PC.2019.8815029</a>
Alternative languages
Result language
angličtina
Original language name
Parameter Estimation in Linear Dynamic Systems using Bayesian networks
Original language description
Parameter estimation in models of dynamic systems is a common preliminary procedure in control, monitoring, fault detection and diagnosis. A range of tools to fulfill this task has been constantly expanded with new additions to meet the increasing demands of modern technological processes. This article proposes the use of Bayesian networks to estimate the parameters of linear dynamic systems described by a state-space model. The proposed approach is used for system identification of two simulated dynamic systems. The parameters are estimated using a learning function for Bayesian networks from Bayes Net Toolbox for Matlab. The results indicate that Bayesian networks can be used as a system identification tool that can compete with conventional methods. However, the approach requires further research aiming to increase convergence of estimates and eliminate numerical problems.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
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 2019 22nd International Conference on Process Control
ISBN
978-1-72813-758-2
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
203-208
Publisher name
IEEE
Place of publication
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Event location
Štrbské Pleso
Event date
Jan 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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