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dc.contributor.authorSalazar Cortés, Jean Carlo
dc.contributor.authorWeber, Philipe
dc.contributor.authorNejjari Akhi-Elarab, Fatiha
dc.contributor.authorSarrate Estruch, Ramon
dc.contributor.authorTheilliol, Didier
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2017-12-12T13:11:41Z
dc.date.available2017-12-12T13:11:41Z
dc.date.issued2017-11-01
dc.identifier.citationSalazar, J., Weber, P., Nejjari, F., Sarrate, R., Theilliol, D. System reliability aware model predictive control framework. "Reliability engineering and system safety", 1 Novembre 2017, vol. 167, p. 663-672.
dc.identifier.issn0951-8320
dc.identifier.urihttp://hdl.handle.net/2117/111780
dc.description.abstractThis paper presents a Model Predictive Control (MPC) framework taking into account the usage of the actuators to preserve system reliability while maximizing control performance. Two approaches are proposed to preserve system reliability: a global approach that integrates in the control algorithm a representation of system reliability, and a local approach that integrates a representation of component reliability. The trade-off between the system reliability and the control performance should be taken into account. A methodology for MPC tuning is proposed to handle this trade-off. System and component reliability are computed based on Dynamic Bayesian Network. The effectiveness and benefits of the proposed control framework are discussed through its application to an over-actuated system.
dc.format.extent10 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject.lcshReliability
dc.subject.lcshBayesian statistical decision theory
dc.subject.lcshAutomatic control
dc.subject.otherReliability
dc.subject.otherDynamic Bayesian networks
dc.subject.otherModel Predictive Control
dc.subject.otherReliability Importance Measures
dc.subject.otherHealth-Aware Control
dc.titleSystem reliability aware model predictive control framework
dc.typeArticle
dc.subject.lemacFidelitat
dc.subject.lemacEstadística bayesiana
dc.subject.lemacControl automàtic
dc.contributor.groupUniversitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control
dc.contributor.groupUniversitat Politècnica de Catalunya. SIC - Sistemes Intel·ligents de Control
dc.identifier.doi10.1016/j.ress.2017.04.012
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S0951832017304416?via%3Dihub
dc.rights.accessOpen Access
drac.iddocument21627575
dc.description.versionPostprint (published version)
upcommons.citation.authorSalazar, J., Weber, P., Nejjari, F., Sarrate, R., Theilliol, D.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameReliability engineering and system safety
upcommons.citation.volume167
upcommons.citation.startingPage663
upcommons.citation.endingPage672


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