Application of mixed integer nonlinear programming for system identification
| Main Author: | |
|---|---|
| Publication Date: | 2020 |
| Other Authors: | , |
| 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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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 |
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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 |
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conference object |
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info:eu-repo/semantics/publishedVersion |
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publishedVersion |
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http://hdl.handle.net/10198/27255 |
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http://hdl.handle.net/10198/27255 |
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eng |
| language |
eng |
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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 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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AIP Publishing |
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AIP Publishing |
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