New offset-free method for model predictive control of open channels
Autor: | Eduard Galvis, Klaudia Horváth, José Rodellar, Manuel Gómez Valentín |
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Přispěvatelé: | Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental, Universitat Politècnica de Catalunya. Departament de Matemàtiques, Universitat Politècnica de Catalunya. FLUMEN - Dinàmica Fluvial i Enginyeria Hidrològica, Universitat Politècnica de Catalunya. CoDAlab - Control, Modelització, Identificació i Aplicacions |
Jazyk: | angličtina |
Rok vydání: | 2015 |
Předmět: |
Automatic control
Engineering Steady state (electronics) Offset (computer science) Experimental canal business.industry Applied Mathematics Internal model Control engineering Computer Science Applications Model predictive control Control and Systems Engineering Control theory Offset-free Component (UML) Canals -- Control Benchmark (computing) Open-channel flow Integrator resonance Enginyeria civil::Enginyeria hidràulica marítima i sanitària::Canals i regadius [Àrees temàtiques de la UPC] Electrical and Electronic Engineering business Irrigation |
Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) Recercat. Dipósit de la Recerca de Catalunya instname |
DOI: | 10.1016/j.conengprac.2015.04.002 |
Popis: | Irrigation or drainage canals can be controlled by model predictive control (MPC). Applying MPC with an internal model in the presence of unknown disturbances in some cases can lead to steady state offset. Therefore an additional component should be implemented along with the MPC. A new method eliminating the offset has been developed in this paper for MPC. It is based on combining two basic approaches of MPC. It has been implemented to control water levels in the three-pool UPC laboratory canal and further numerically tested using a test case benchmark proposed by the American Society of Civil Engineers (ASCE). It has been found that the developed offset-free method is able to eliminate the steady-state offset, while taking into account known and unknown disturbances. |
Databáze: | OpenAIRE |
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