Policy search for active fault diagnosis with partially observable state

dc.contributor.authorKrál, Ladislav
dc.contributor.authorPunčochář, Ivo
dc.date.accessioned2023-01-02T11:00:09Z
dc.date.available2023-01-02T11:00:09Z
dc.date.issued2022
dc.description.abstract-translatedThe article deals with a novel design of an active fault detector (AFD) for a nonlinear stochastic system with a partially observable state. The imperfect state information problem is converted to a perfect state information problem using a state estimator. Subsequently, the problem is decomposed into separate tasks of an optimal fault detector design and an approximate input generator design using a dynamic programming technique. While the former task is straightforward, the latter represents a nonlinear functional optimization problem. The input generator is approximated by a multi-layer perceptron neural network, and its unknown parameters are found using the policy search method. Effectiveness of the proposed AFD design is demonstrated numerically on a pendulum system and a heating/cooling system.en
dc.format27 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.citationKRÁL, L. PUNČOCHÁŘ, I. Policy search for active fault diagnosis with partially observable state. International Journal of Adaptive Control and Signal Processing, 2022, roč. 36, č. 9, s. 2190-2216. ISSN: 0890-6327cs
dc.identifier.document-number811389500001
dc.identifier.doi10.1002/acs.3456
dc.identifier.issn0890-6327
dc.identifier.obd43936811
dc.identifier.uri2-s2.0-85131886551
dc.identifier.urihttp://hdl.handle.net/11025/50799
dc.language.isoenen
dc.project.IDGA18-08531S/Aktivní přístup k detekci poruch ve stochastických rozlehlých systémechcs
dc.project.IDSGS-2022-022/Rozvoj a využití kybernetických systémů identifikace, diagnostiky a řízení 5cs
dc.publisherWileyen
dc.relation.ispartofseriesInternational Journal of Adaptive Control and Signal Processingen
dc.rightsPlný text je přístupný v rámci univerzity přihlášeným uživatelům.cs
dc.rights© Wileyen
dc.rights.accessrestrictedAccessen
dc.subject.translatedapproximate dynamic programmingen
dc.subject.translatedfault detectionen
dc.subject.translatedneural networksen
dc.subject.translatedreinforcement learningen
dc.subject.translatedstate estimationen
dc.titlePolicy search for active fault diagnosis with partially observable stateen
dc.typečlánekcs
dc.typearticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen

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