Time-instant optimization for hybrid model predictive control of the Rhine-Meuse delta.
Saved in:
| Title: | Time-instant optimization for hybrid model predictive control of the Rhine-Meuse delta. |
|---|---|
| Authors: | van Ekeren, H.1 r.r.negenborn@tudetft.nl, Negenborn, R. R.2, van Overloop, P. J.3, De Schutter, B.1 |
| Source: | Journal of Hydroinformatics. Apr2013, Vol. 15 Issue 2, p271-292. 22p. |
| Subjects: | Backwater, Predictive control systems, Mathematical optimization, Hybrid systems, Simulation methods & models |
| Geographic Terms: | Rhine-Meuse Delta (Netherlands), Netherlands |
| Abstract: | In order to ensure safety against high sea water levels, in many low-lying countries, water levels are maintained at certain safety levels, and dikes have been built, while large control structures have been installed that can also be adjusted dynamically after they have been constructed. Currently, these control structures are often operated purely locally, without coordination of actions being taken at different locations. Automatically coordinating these actions is difficult, as open water systems are complex, hybrid dynamical systems, in the sense that continuous dynamics (e.g. the evolution of the water levels) appear mixed with discrete events (e.g. the opening or closing of barriers). In low lands, this complexity is increased further due to bi-directional water flows resulting from backwater effects and interconnectivity of flows in different parts of river deltas. In this paper, we propose a model predictive control (MPC) approach that is aimed at automatically coordinating the actions of control structures. The hybrid dynamical nature of the water system is explicitly taken into account, in order to relieve the computational complexity involved in solving the MPC problem, we propose TIO-MPC, where TIO stands for time-instant optimization. Using this approach, the original MPC optimization problem that uses both continuous and integer variables is transformed into a problem involving only continuous variables. Simulation studies of current and future situations are used to illustrate the behavior of the proposed scheme. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Hydroinformatics is the property of IWA Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 87402821 AccessLevel: 6 PubType: Periodical PubTypeId: serialPeriodical PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Time-instant optimization for hybrid model predictive control of the Rhine-Meuse delta. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22van+Ekeren%2C+H%2E%22">van Ekeren, H.</searchLink><relatesTo>1</relatesTo><i> r.r.negenborn@tudetft.nl</i><br /><searchLink fieldCode="AR" term="%22Negenborn%2C+R%2E+R%2E%22">Negenborn, R. R.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22van+Overloop%2C+P%2E+J%2E%22">van Overloop, P. J.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22De+Schutter%2C+B%2E%22">De Schutter, B.</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Hydroinformatics%22">Journal of Hydroinformatics</searchLink>. Apr2013, Vol. 15 Issue 2, p271-292. 22p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Backwater%22">Backwater</searchLink><br /><searchLink fieldCode="DE" term="%22Predictive+control+systems%22">Predictive control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Hybrid+systems%22">Hybrid systems</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Rhine-Meuse+Delta+%28Netherlands%29%22">Rhine-Meuse Delta (Netherlands)</searchLink><br /><searchLink fieldCode="DE" term="%22Netherlands%22">Netherlands</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In order to ensure safety against high sea water levels, in many low-lying countries, water levels are maintained at certain safety levels, and dikes have been built, while large control structures have been installed that can also be adjusted dynamically after they have been constructed. Currently, these control structures are often operated purely locally, without coordination of actions being taken at different locations. Automatically coordinating these actions is difficult, as open water systems are complex, hybrid dynamical systems, in the sense that continuous dynamics (e.g. the evolution of the water levels) appear mixed with discrete events (e.g. the opening or closing of barriers). In low lands, this complexity is increased further due to bi-directional water flows resulting from backwater effects and interconnectivity of flows in different parts of river deltas. In this paper, we propose a model predictive control (MPC) approach that is aimed at automatically coordinating the actions of control structures. The hybrid dynamical nature of the water system is explicitly taken into account, in order to relieve the computational complexity involved in solving the MPC problem, we propose TIO-MPC, where TIO stands for time-instant optimization. Using this approach, the original MPC optimization problem that uses both continuous and integer variables is transformed into a problem involving only continuous variables. Simulation studies of current and future situations are used to illustrate the behavior of the proposed scheme. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Hydroinformatics is the property of IWA Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=87402821 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.2166/hydro.2013.177 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 271 Subjects: – SubjectFull: Backwater Type: general – SubjectFull: Predictive control systems Type: general – SubjectFull: Mathematical optimization Type: general – SubjectFull: Hybrid systems Type: general – SubjectFull: Simulation methods & models Type: general – SubjectFull: Rhine-Meuse Delta (Netherlands) Type: general – SubjectFull: Netherlands Type: general Titles: – TitleFull: Time-instant optimization for hybrid model predictive control of the Rhine-Meuse delta. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: van Ekeren, H. – PersonEntity: Name: NameFull: Negenborn, R. R. – PersonEntity: Name: NameFull: van Overloop, P. J. – PersonEntity: Name: NameFull: De Schutter, B. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2013 Type: published Y: 2013 Identifiers: – Type: issn-print Value: 14647141 Numbering: – Type: volume Value: 15 – Type: issue Value: 2 Titles: – TitleFull: Journal of Hydroinformatics Type: main |
| ResultId | 1 |
