Application of mixed integer nonlinear programming for system identification

Bibliographic Details
Main Author: Fernandes, Natércia C.P.
Publication Date: 2020
Other Authors: Fernandes, Florbela P., Romanenko, Andrey
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10198/27255
Summary: This work describes a method of deadtime approximation in dynamic systems, particularly in the context of nonlinear model predictive control based on mechanistic models where the differentiability of the equations must be ensured. The resulting system identification system is solved using the BBMCSFilter (Branch and Bound based on a Multistart Coordinate Search Filter) global optimization algorithm to determine the order and the parameters of the resulting model, taking into account not only the model-plant mismatch but also the model complexity and the resulting computation time. The application of the method is illustrated with a simulated example of a chemical process unit. © 2020 American Institute of Physics Inc.. All rights reserved.
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spelling Application of mixed integer nonlinear programming for system identificationThis work describes a method of deadtime approximation in dynamic systems, particularly in the context of nonlinear model predictive control based on mechanistic models where the differentiability of the equations must be ensured. The resulting system identification system is solved using the BBMCSFilter (Branch and Bound based on a Multistart Coordinate Search Filter) global optimization algorithm to determine the order and the parameters of the resulting model, taking into account not only the model-plant mismatch but also the model complexity and the resulting computation time. The application of the method is illustrated with a simulated example of a chemical process unit. © 2020 American Institute of Physics Inc.. All rights reserved.This work was supported by Fundac¸ao para a Ciência e a Tecnologia, UID/EQU/00102/2019. The first author also thanks project MATIS, ref. CENTRO-01-0145-FEDER-000014, with financial support of ERDF (CENTRO2020).AIP PublishingBiblioteca Digital do IPBFernandes, Natércia C.P.Fernandes, Florbela P.Romanenko, Andrey2023-02-27T16:36:54Z20202020-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10198/27255engFernandes, Natércia C.P.; Fernandes, Florbela P.; Romanenko, Andrey (2020). Application of mixed integer nonlinear programming for system identification. In International Conference on Numerical Analysis and Applied Mathematics 2019, ICNAAM 2019. Rhodes10.1063/5.0026410info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-25T12:18:26Zoai:bibliotecadigital.ipb.pt:10198/27255Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T11:46:00.781594Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Application of mixed integer nonlinear programming for system identification
title Application of mixed integer nonlinear programming for system identification
spellingShingle Application of mixed integer nonlinear programming for system identification
Fernandes, Natércia C.P.
title_short Application of mixed integer nonlinear programming for system identification
title_full Application of mixed integer nonlinear programming for system identification
title_fullStr Application of mixed integer nonlinear programming for system identification
title_full_unstemmed Application of mixed integer nonlinear programming for system identification
title_sort Application of mixed integer nonlinear programming for system identification
author Fernandes, Natércia C.P.
author_facet Fernandes, Natércia C.P.
Fernandes, Florbela P.
Romanenko, Andrey
author_role author
author2 Fernandes, Florbela P.
Romanenko, Andrey
author2_role author
author
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.contributor.author.fl_str_mv Fernandes, Natércia C.P.
Fernandes, Florbela P.
Romanenko, Andrey
description This work describes a method of deadtime approximation in dynamic systems, particularly in the context of nonlinear model predictive control based on mechanistic models where the differentiability of the equations must be ensured. The resulting system identification system is solved using the BBMCSFilter (Branch and Bound based on a Multistart Coordinate Search Filter) global optimization algorithm to determine the order and the parameters of the resulting model, taking into account not only the model-plant mismatch but also the model complexity and the resulting computation time. The application of the method is illustrated with a simulated example of a chemical process unit. © 2020 American Institute of Physics Inc.. All rights reserved.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-01-01T00:00:00Z
2023-02-27T16:36:54Z
dc.type.driver.fl_str_mv conference object
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10198/27255
url http://hdl.handle.net/10198/27255
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Fernandes, Natércia C.P.; Fernandes, Florbela P.; Romanenko, Andrey (2020). Application of mixed integer nonlinear programming for system identification. In International Conference on Numerical Analysis and Applied Mathematics 2019, ICNAAM 2019. Rhodes
10.1063/5.0026410
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv AIP Publishing
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