Parameter Estimation in Linear Dynamic Systems using Bayesian networks

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dc.contributor.authorGaran, Maryna
dc.contributor.authorVerron, Sylvain
dc.contributor.authorKovalenko, Iaroslav
dc.contributor.authorModrlak, Osvald
dc.contributor.authorLepšík, Petr
dc.date.accessioned2019-10-01T08:49:24Z
dc.date.available2019-10-01T08:49:24Z
dc.date.issued2019-06
dc.description.abstractParameter 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.cs
dc.format.extent6 strancs
dc.identifier.doi10.1109/PC.2019.8815029
dc.identifier.urihttps://dspace.tul.cz/handle/15240/153805
dc.identifier.urihttps://ieeexplore.ieee.org/document/8815029
dc.language.isocscs
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofProceedings of the 2019 22nd International Conference on Process Control, PC 2019
dc.subjectBayes Net Toolboxcs
dc.subjectBayesian networkcs
dc.subjectstate-space modelcs
dc.subjectsystem identificationcs
dc.titleParameter Estimation in Linear Dynamic Systems using Bayesian networkscs
dc.typeConference Paper
local.article.number8815029
local.citation.epage208
local.citation.spage203
local.event.edate2019-06-14
local.event.locationStrbske Pleso; Slovakia
local.event.sdate2019-06-11
local.event.title22nd International Conference on Process Control, PC 2019
local.identifier.publikace6706
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