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Combining CSP and MPC for the operational control of water networks

AutorSun, Congcong; Puig, Vicenç; Cembrano, Gabriela
Palabras claveCSP
Water networks
Epanet
MPC
Fecha de publicación2016
EditorElsevier
CitaciónEngineering Applications of Artificial Intelligence 49: 126-140 (2016)
ResumenThis paper presents a control scheme which uses a combination of linear Model Predictive Control (MPC) and a Constraint Satisfaction Problem (CSP) to solve the non-linear operational optimal control of Drinking Water Networks (DWNs). The methodology has been divided into two functional layers: first, a CSP algorithm is used to transfer non-linear DWNs pressure equations into linear constraints on flows and tank volumes, which can enclose the feasible solution set of the hydraulic non-linear problem during the optimization process. Then, a linear MPC with tightened constraints produced in the CSP layer is solved to generate control strategies which optimize the control objectives. The proposed approach is simulated using Epanet to represent the real DWNs. Non-linear MPC is used for validation. To illustrate the performance of the proposed approach, a case study based on the Richmond water network is used and a realistic example, D-Town benchmark network, is added as a supplementary case study.
Versión del editorhttp://dx.doi.org/10.1016/j.engappai.2015.12.006
URIhttp://hdl.handle.net/10261/132943
DOI10.1016/j.engappai.2015.12.006
Identificadoresdoi: 10.1016/j.engappai.2015.12.006
issn: 0952-1976
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