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Output-feedback model predictive control of sewer networks through moving horizon estimation
dc.contributor.author | Joseph Duran, Bernat |
dc.contributor.author | Ocampo-Martínez, Carlos |
dc.contributor.author | Cembrano Gennari, Gabriela |
dc.contributor.other | Institut de Robòtica i Informàtica Industrial |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2015-07-08T17:47:25Z |
dc.date.available | 2015-07-08T17:47:25Z |
dc.date.created | 2014 |
dc.date.issued | 2014 |
dc.identifier.citation | Joseph, B.; Ocampo-Martinez, C.A.; Cembrano, M. Output-feedback model predictive control of sewer networks through moving horizon estimation. A: IEEE Conference on Decision and Control. "2014 IEEE 53rd Annual Conference on Decision and Control (CDC)". Los Angeles: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 1061-1066. |
dc.identifier.isbn | 978-1-4799-7746-8 |
dc.identifier.uri | http://hdl.handle.net/2117/28546 |
dc.description.abstract | Based on a simplified control-oriented hybrid linear delayed model, model predictive control (MPC) of a sewer network designed to reduce pollution during heavy rain events is presented. The lack of measurements at many parts of the system to update the initial conditions of the optimal control problems (OCPs) leads to the need for estimation techniques. A simple modification of the OCP used in the MPC iterations allows to formulate a state estimation problem (SEP) to reconstruct the full system state from a few measurements. Results comparing the system performance under the MPC controller using full-state measurements and a moving horizon estimation (MHE) strategy solving a finite horizon SEP at each time instant are presented. Closed-loop simulations are performed by using a detailed physically-based model of the network as virtual reality. |
dc.format.extent | 6 p. |
dc.language.iso | eng |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
dc.subject.other | observability |
dc.subject.other | optimisation |
dc.subject.other | predictive control |
dc.subject.other | receding horizon control |
dc.subject.other | moving horizon estimation |
dc.subject.other | sewer networks |
dc.subject.other | optimal control |
dc.subject.other | state estimation. |
dc.title | Output-feedback model predictive control of sewer networks through moving horizon estimation |
dc.type | Conference report |
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 | 10.1109/CDC.2014.7039522 |
dc.description.peerreviewed | Peer Reviewed |
dc.subject.inspec | Classificació INSPEC::Control theory::Optimal control |
dc.relation.publisherversion | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7039522 |
dc.rights.access | Open Access |
local.identifier.drac | 15446706 |
dc.description.version | Postprint (author’s final draft) |
local.citation.author | Joseph, B.; Ocampo-Martinez, C.A.; Cembrano, M. |
local.citation.contributor | IEEE Conference on Decision and Control |
local.citation.pubplace | Los Angeles |
local.citation.publicationName | 2014 IEEE 53rd Annual Conference on Decision and Control (CDC) |
local.citation.startingPage | 1061 |
local.citation.endingPage | 1066 |