Digital Twin of Calais Canal with Model Predictive Controller

A Simulation on a Real Database

Journal Article (2024)
Author(s)

R. Ranjbar (Institut Mines-Telecom)

P. Segovia Castillo (TU Delft - Transport Engineering and Logistics)

Eric Duviella (Institut Mines-Telecom)

Lucien Etienne (Institut Mines-Telecom)

Jose Maria Maestre (University of Seville)

Eduardo F. Camacho (University of Seville)

Research Group
Transport Engineering and Logistics
Copyright
© 2024 Roza Ranjbar, P. Segovia Castillo, Eric Duviella, Lucien Etienne, José M. Maestre, Eduardo F. Camacho
DOI related publication
https://doi.org/10.1061/JWRMD5.WRENG-6266
More Info
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Publication Year
2024
Language
English
Copyright
© 2024 Roza Ranjbar, P. Segovia Castillo, Eric Duviella, Lucien Etienne, José M. Maestre, Eduardo F. Camacho
Research Group
Transport Engineering and Logistics
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
5
Volume number
150
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Abstract

This paper presents the design of a model predictive control (MPC) for the Calais canal, located in the north of France for satisfactory management of the system. To estimate the unknown inputs/outputs arising from the uncontrolled pumps, a digital twin (DT) in the framework of a Matlab-SIC2 is used to reproduce the dynamics of the canal, and the real database corresponding to a period of three days is employed to evaluate the control strategy. The canal is characterized by two operating modes due to high and low tides. As a consequence of this, time-varying constraints on the use of gates must be considered, which leads to the design of two multiobjective control problems, one for the high tide and another for the low tide. Furthermore, a moving horizon estimation (MHE) strategy is used to provide the MPC with unmeasured states. The simulation results show that the different objectives are met satisfactorily.

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