Active Fault Detection Based on Tensor Train Decomposition

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F24%3A00598043" target="_blank" >RIV/67985556:_____/24:00598043 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S2405896324003811?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2405896324003811?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ifacol.2024.07.297" target="_blank" >10.1016/j.ifacol.2024.07.297</a>

Result language
angličtina
Original language name
Active Fault Detection Based on Tensor Train Decomposition
Original language description
The paper deals with the use of tensor train decomposition for active fault detection of stochastic systems. The faulty and faulty-free behavior of the system is represented using multiple models. A non-rectangular grid in the space of the information state is proposed. An approximate Bellman function is represented using the tensor train decomposition and is calculated using the value iteration algorithm.
Czech name
—
Czech description
—

Project
<a href="/en/project/GA22-11101S" target="_blank" >GA22-11101S: Tensor Decomposition in Active Fault Diagnosis for Stochastic Large Scale Systems</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
IFAC-PapersOnLine. Volume 58, Issue 4 -12th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2024
ISBN
—
ISSN
2405-8963
e-ISSN
—
Number of pages
6
Pages from-to
676-681
Publisher name
Elsevier
Place of publication
Amsterdam
Event location
Ferrara
Event date
Jun 4, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001296047100114

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