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Learning-based tuning of supervisory model predictive control for drinking water networks
dc.contributor.author | Grosso Pérez, Juan Manuel |
dc.contributor.author | Ocampo-Martínez, Carlos |
dc.contributor.author | Puig Cayuela, Vicenç |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2013-10-04T08:54:22Z |
dc.date.available | 2013-10-04T08:54:22Z |
dc.date.created | 2013 |
dc.date.issued | 2013 |
dc.identifier.citation | Grosso, J.; Ocampo-Martinez, C.A.; Puig, V. Learning-based tuning of supervisory model predictive control for drinking water networks. "Engineering applications of artificial intelligence", 2013, vol. 26, núm. 7, p. 1741-1750. |
dc.identifier.issn | 0952-1976 |
dc.identifier.uri | http://hdl.handle.net/2117/20298 |
dc.description.abstract | This paper presents a constrained Model Predictive Control (MPC) strategy enriched with soft-control techniques as neural networks and fuzzy logic, to incorporate self-tuning capabilities and reliability aspects for the management of drinking water networks (DWNs). The control system architecture consists in a multilayer controller with three hierarchical layers: learning and planning layer, supervision and adaptation layer, and feedback control layer. Results of applying the proposed approach to the Barcelona DWN show that the quasi-explicit nature of the proposed adaptive predictive controller leads to improve the computational time, especially when the complexity of the problem structure can vary while tuning the receding horizons. |
dc.format.extent | 10 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
dc.subject | Àrees temàtiques de la UPC::Enginyeria civil::Enginyeria hidràulica, marítima i sanitària::Enginyeria sanitària |
dc.subject.lcsh | Drinking water networks |
dc.subject.lcsh | Drinking water -- Spain -- Barcelona |
dc.subject.other | Drinking water networks |
dc.subject.other | Fuzzy-logic |
dc.subject.other | Model predictive control |
dc.subject.other | Multilayer controller |
dc.subject.other | Neural networks |
dc.subject.other | Self-tuning |
dc.title | Learning-based tuning of supervisory model predictive control for drinking water networks |
dc.type | Article |
dc.subject.lemac | Aigua potable -- Abastament -- Control automàtic |
dc.contributor.group | Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control |
dc.identifier.doi | 10.1016/j.engappai.2013.03.003 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://www.sciencedirect.com/science/article/pii/S0952197613000390 |
dc.rights.access | Open Access |
local.identifier.drac | 12466849 |
dc.description.version | Preprint |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/FP7/318556/EU/Efficient Integrated Real-time Monitoring and Control of Drinking Water Networks/EFFINET |
dc.relation.projectid | info:eu-repo/grantAgreement/MICINN//DPI2009-13744/ES/Analisis Y Diseño De Estrategidas De Control Optimo Distribuido Aplicadas A La Gestion De Sistemas De Agua De Gran Escala/ |
local.citation.author | Grosso, J.; Ocampo-Martinez, C.A.; Puig, V. |
local.citation.publicationName | Engineering applications of artificial intelligence |
local.citation.volume | 26 |
local.citation.number | 7 |
local.citation.startingPage | 1741 |
local.citation.endingPage | 1750 |
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