2024-03-29T10:15:40Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1352892022-02-07T15:43:01Zcom_10366_135275com_10366_4512com_10366_3823com_10366_4386com_10366_4349com_10366_3946col_10366_135276col_10366_4387
00925njm 22002777a 4500
dc
Francisco Sutil, Mario
author
Skogestad, Sigurd
author
Vega Cruz, Pastora Isabel
author
2015
[EN] This paper describes a procedure to find the best controlled variables in an economic sense for the activated sludge process in a wastewater treatment plant, despite the large load disturbances. A novel dynamic analysis of the closed loop control of these variables has been performed, considering a nonlinear model predictive controller (NMPC) and a particular distributed NMPC-PI control structure where the PI is devoted to control the process active constraints and the NMPC the self-optimizing variables. The well-known self-optimizing control methodology has been applied, considering the most important measurements of the process. This methodology provides the optimum combination of measurements to keep constant with minimum economic loss. In order to avoid non feasible dynamic operation, a preselection of the measurements has been performed, based on the nonlinear model of the process and evaluating the possibility of keeping their values constant in the presence of typical disturbances.
[ES] Este trabajo describe un procedimiento eficiente para encontrar las mejores variables para el proceso de lodos activados en una planta de tratamiento de aguas residuales, a pesar de las grandes perturbaciones de carga. Se ha realizado un nuevo análisis dinámico del control en bucle cerrado de estas variables, considerando un controlador predictivo de modelo no lineal (NMPC) y una estructura de control NMPC-PI distribuida. Se ha aplicado la conocida metodología de control de auto-optimización, considerando las mediciones más importantes del proceso. Esta metodología proporciona la combinación óptima de mediciones para mantener constante con pérdidas económicas mínimas. Para evitar un funcionamiento dinámico no factible, se ha realizado una preselección de las mediciones, basándose en el modelo no lineal del proceso y evaluando la posibilidad de mantener constantes sus valores en presencia de perturbaciones típicas.
Francisco, M., Skogestad, S., Vega, P. (2015). Model predictive control for the self-optimized operation in wastewater treatment plant : analysis of dynamic issues.Computers & Chemical Engineering, 82, pp. 259-272
http://hdl.handle.net/10366/135289
Self-optimizing control
Electrical engineering, electronics and photonics
Chemical engineering
Proceso de optimización
Process optimization
Activated sludge process
Model predictive control, MPC
Wasterwater treatment plants
Tratamiento de lodos activados
Model predictive control for the self-optimized operation in wastewater treatment plant : analysis of dynamic issues