De Saint-Venant equations-based model assessment in model predictive control of open channel flow
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| Title: | De Saint-Venant equations-based model assessment in model predictive control of open channel flow |
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| Authors: | Xu, M.1 min.xu@tudelft.nl, Negenborn, R.R.2, van Overloop, P.J.1, van de Giesen, N.C.1 |
| Source: | Advances in Water Resources. Dec2012, Vol. 49, p37-45. 9p. |
| Subjects: | Channel flow, Mathematical optimization, Prediction models, Optimal control theory, Linear statistical models, Estimation theory, Quadratic programming, Linear time invariant systems |
| Abstract: | Abstract: Model predictive control (MPC) is a model-based control technique that uses an optimization algorithm to generate optimal control actions. Based on the model used in optimization, MPC approaches can be categorized as linear or nonlinear. Both classes have advantages and disadvantages in terms of control accuracy and computational time. A typical linear model in open channel water management is the Integrator Delay (ID) model, while a nonlinear model usually refers to the Saint-Venant equations. In earlier work, we proposed the use of linearized Saint-Venant equations for MPC, where the model is formulated in a linear time-varying format and time-varying parameters are estimated outside of the optimization. Quadratic Programming (QP) is used to solve the optimization problem. However, the control accuracy of such an MPC scheme is not clear. In this paper, we compare this approach with an MPC scheme that uses Sequential Quadratic Programming (SQP) to solve the optimization problem. Because the estimation of the time-varying parameters is integrated in the optimization in SQP, the solutions from SQP-based MPC are expected to be superior to the solutions of QP-based approach. However, SQP can be computationally expensive. A simulation experiment illustrates that the QP-based MPC approach using a linearized Saint-Venant model has an accurate approximation of the control performance of SQP. [Copyright &y& Elsevier] |
| Copyright of Advances in Water Resources is the property of Elsevier B.V. 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 |
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| Header | DbId: egs DbLabel: Engineering Source An: 82685833 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: De Saint-Venant equations-based model assessment in model predictive control of open channel flow – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Xu%2C+M%2E%22">Xu, M.</searchLink><relatesTo>1</relatesTo><i> min.xu@tudelft.nl</i><br /><searchLink fieldCode="AR" term="%22Negenborn%2C+R%2ER%2E%22">Negenborn, R.R.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22van+Overloop%2C+P%2EJ%2E%22">van Overloop, P.J.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22van+de+Giesen%2C+N%2EC%2E%22">van de Giesen, N.C.</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Advances+in+Water+Resources%22">Advances in Water Resources</searchLink>. Dec2012, Vol. 49, p37-45. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Channel+flow%22">Channel flow</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink><br /><searchLink fieldCode="DE" term="%22Optimal+control+theory%22">Optimal control theory</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+statistical+models%22">Linear statistical models</searchLink><br /><searchLink fieldCode="DE" term="%22Estimation+theory%22">Estimation theory</searchLink><br /><searchLink fieldCode="DE" term="%22Quadratic+programming%22">Quadratic programming</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+time+invariant+systems%22">Linear time invariant systems</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Abstract: Model predictive control (MPC) is a model-based control technique that uses an optimization algorithm to generate optimal control actions. Based on the model used in optimization, MPC approaches can be categorized as linear or nonlinear. Both classes have advantages and disadvantages in terms of control accuracy and computational time. A typical linear model in open channel water management is the Integrator Delay (ID) model, while a nonlinear model usually refers to the Saint-Venant equations. In earlier work, we proposed the use of linearized Saint-Venant equations for MPC, where the model is formulated in a linear time-varying format and time-varying parameters are estimated outside of the optimization. Quadratic Programming (QP) is used to solve the optimization problem. However, the control accuracy of such an MPC scheme is not clear. In this paper, we compare this approach with an MPC scheme that uses Sequential Quadratic Programming (SQP) to solve the optimization problem. Because the estimation of the time-varying parameters is integrated in the optimization in SQP, the solutions from SQP-based MPC are expected to be superior to the solutions of QP-based approach. However, SQP can be computationally expensive. A simulation experiment illustrates that the QP-based MPC approach using a linearized Saint-Venant model has an accurate approximation of the control performance of SQP. [Copyright &y& Elsevier] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Advances in Water Resources is the property of Elsevier B.V. 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.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.advwatres.2012.07.004 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 37 Subjects: – SubjectFull: Channel flow Type: general – SubjectFull: Mathematical optimization Type: general – SubjectFull: Prediction models Type: general – SubjectFull: Optimal control theory Type: general – SubjectFull: Linear statistical models Type: general – SubjectFull: Estimation theory Type: general – SubjectFull: Quadratic programming Type: general – SubjectFull: Linear time invariant systems Type: general Titles: – TitleFull: De Saint-Venant equations-based model assessment in model predictive control of open channel flow Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Xu, M. – PersonEntity: Name: NameFull: Negenborn, R.R. – PersonEntity: Name: NameFull: van Overloop, P.J. – PersonEntity: Name: NameFull: van de Giesen, N.C. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2012 Type: published Y: 2012 Identifiers: – Type: issn-print Value: 03091708 Numbering: – Type: volume Value: 49 Titles: – TitleFull: Advances in Water Resources Type: main |
| ResultId | 1 |
