Ouput-feedback control of combined sewer networks through receding horizon control with moving horizon estimation
An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/84090 |
| Acceso en línea: | https://hdl.handle.net/2117/84090 https://dx.doi.org/10.1002/2014WR016696 |
| Access Level: | acceso abierto |
| Palabra clave: | control system synthesis observability optimisation predictive control output-feedback control moving horizon estimators sewer networks urban water cycle Classificació INSPEC::Optimisation Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
| Sumario: | An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solving these problems, preliminary Receding Horizon Control with Moving Horizon Estimation (RHC/MHE) results, based on flow measurements, were also obtained. In this work, the RHC/MHE algorithm has been extended to take into account both flow and water level measurements and the resulting control loop has been extensively simulated to assess the system performance according to different measurement availability scenarios and rain events. All simulations have been carried out using a detailed physically-based model of a real case-study network as virtual reality. |
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