A Multilayer Control Strategy for the Calais Canal

Journal Article (2024)
Author(s)

Pablo Segovia (TU Delft - Transport Engineering and Logistics)

Vicenç Puig (Institut de Ròbotica i Informàtica Industrial, Barcelona, Universitat Politecnica de Catalunya)

Eric Duviella (Université de Lille)

Research Group
Transport Engineering and Logistics
Copyright
© 2024 P. Segovia Castillo, Vicenc Puig, Eric Duviella
DOI related publication
https://doi.org/10.1109/TCST.2023.3309503
More Info
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Publication Year
2024
Language
English
Copyright
© 2024 P. Segovia Castillo, Vicenc Puig, Eric Duviella
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
2
Volume number
32
Pages (from-to)
311-325
Reuse Rights

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Abstract

This article presents the design of a control strategy for the Calais canal, a navigation canal located in a lowland area in northern France that is affected by tides. Moreover, the available actuators are discrete-valued and the hierarchy of operational objectives is time-varying. All these circumstances render water level regulation of the Calais canal a challenging problem. In view of this situation, the design of the overall control architecture is divided into a sequence of structured tasks, which are distributed among layers. The upper layer determines the current operating mode based on the analysis of several environmental and operational aspects. Information regarding the current mode is taken into account at the intermediate layer to select the appropriate optimization-based control problem, which is solved using lexicographic minimization. The optimal control setpoints are determined and sent to the lower layer, where scheduling problems are solved to select low-level control actions from a finite set to minimize the mismatch with respect to the optimal setpoints. Different realistic simulation scenarios are tested to demonstrate the effectiveness of the proposed approach.

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