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Title: Model predictive control combined with Genetic Algorithms for a river system
Authors: Chiang, Po-Kuan
Willems, Patrick
Issue Date: Aug-2014
Host Document: Proceedings of 11th International Conference on Hydroinformatics (HIC 2014) pages:1-8
Conference: 11th International Conference on Hydroinformatics edition:2014 location:New York, USA date:17-21 August 2014
Abstract: Real time flood control becomes more widely applied given its features to make more efficient use of existing storage capacity available in flood control reservoirs. In order to accelerate the large number of iterations concerning the hydraulic computations in optimization procedures, a simplified river conceptual model was developed and connected to a Model Predictive Control (MPC) algorithm. This tool was applied to determine efficient real-time flood control policies for the 12 gated-weirs in the Belgian case study of the river Demer around two main flood control reservoirs. Because the system dynamics are nonlinear (gate openings are considered as inputs in the MPC), the MPC was combined with Genetic Algorithms (GAs) to cope with the nonlinear problems. The MPCGA model searches for better control actions by minimizing the cost function while at the same time avoiding violation of the defined constraints. The optimization results testify that MPCGA is capable of improving the current regulation strategy that is based on fixed regulation rules and three-point controllers.
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Hydraulics Section

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