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Title:Improvement of navigation conditions using Model Predictive Control - The Cuinchy-Fontinettes case study
Authors:K. Horvath, E. Duviella, L. Rajaoarisoa, R.R. Negenborn, K. Chuquet

Conference:6th International Conference on Computational Logistics (ICCL'15)
Address:Delft, The Netherlands
Date:September 2015

Abstract:A 20% shift from road transport to inland navigation and railway is expected by 2050 in France. By focusing on inland navigation, this expected increase of transport will require an efficient management of the infrastructure and water. Inland navigation requires water levels kept within the navigation rectangle. Hence it is necessary to design efficient control algorithms for water levels. Model Predictive Control (MPC) is proposed to regulate the water level of canals with locks. This controller maintains the level close to the navigation objective by rejecting disturbances mainly caused by lock operations. In this paper, MPC is designed by considering realistic constraints on the dynamics of the gates and the available supplied discharges. It allows taking into account several operating conditions that correspond to normal, drought and flood situations. MPC strategy is tested on a numerical simulation of the Cuinchy-Fontinettes reach that is located in the north of France.

Reference:K. Horvath, E. Duviella, L. Rajaoarisoa, R.R. Negenborn, K. Chuquet. Improvement of navigation conditions using Model Predictive Control - The Cuinchy-Fontinettes case study. In Proceedings of the 6th International Conference on Computational Logistics (ICCL'15), Delft, The Netherlands, pp. 222-237, September 2015.
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