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System reliability aware model predictive control framework
dc.contributor.author | Salazar Cortés, Jean Carlo |
dc.contributor.author | Weber, Philipe |
dc.contributor.author | Nejjari Akhi-Elarab, Fatiha |
dc.contributor.author | Sarrate Estruch, Ramon |
dc.contributor.author | Theilliol, Didier |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2017-12-12T13:11:41Z |
dc.date.available | 2017-12-12T13:11:41Z |
dc.date.issued | 2017-11-01 |
dc.identifier.citation | Salazar, 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.issn | 0951-8320 |
dc.identifier.uri | http://hdl.handle.net/2117/111780 |
dc.description.abstract | This 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.extent | 10 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
dc.subject.lcsh | Reliability |
dc.subject.lcsh | Bayesian statistical decision theory |
dc.subject.lcsh | Automatic control |
dc.subject.other | Reliability |
dc.subject.other | Dynamic Bayesian networks |
dc.subject.other | Model Predictive Control |
dc.subject.other | Reliability Importance Measures |
dc.subject.other | Health-Aware Control |
dc.title | System reliability aware model predictive control framework |
dc.type | Article |
dc.subject.lemac | Fidelitat |
dc.subject.lemac | Estadística bayesiana |
dc.subject.lemac | Control automàtic |
dc.contributor.group | Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control |
dc.contributor.group | Universitat Politècnica de Catalunya. SIC - Sistemes Intel·ligents de Control |
dc.identifier.doi | 10.1016/j.ress.2017.04.012 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://www.sciencedirect.com/science/article/pii/S0951832017304416?via%3Dihub |
dc.rights.access | Open Access |
local.identifier.drac | 21627575 |
dc.description.version | Postprint (published version) |
local.citation.author | Salazar, J.; Weber, P.; Nejjari, F.; Sarrate, R.; Theilliol, D. |
local.citation.publicationName | Reliability engineering and system safety |
local.citation.volume | 167 |
local.citation.startingPage | 663 |
local.citation.endingPage | 672 |
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