BlueM.MPC: Difference between revisions
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{{BlueM.MPC nav }} | |||
[[File:BlueMMPC_UserForm.png|thumb|User form of BlueM.MPC]] | [[File:BlueMMPC_UserForm.png|thumb|User form of BlueM.MPC]] | ||
==Description== | ==Description== | ||
BlueM.MPC is a software for the simulation of model predictive control (MPC) in sewer networks. MPC is an online strategy for real time control (RTC). Control decisions are calculated during operation with a process model and optimization algorithms. This feature distinguishes MPC from off-line control strategies, in which the control decisions are calculated during the design phase. These control decisions are usually stored in a database (rule-based control) and are available during operation without delay. BlueM.MPC implements [[SWMM | SWMM5]] for process modelling and [[BlueM.Opt | BlueM.Opt]] for optimization. | BlueM.MPC is a software for the simulation of model predictive control (MPC) in sewer networks. MPC is an online strategy for real time control (RTC). Control decisions are calculated during operation with a process model and optimization algorithms. This feature distinguishes MPC from off-line control strategies, in which the control decisions are calculated during the design phase. These control decisions are usually stored in a database (rule-based control) and are available during operation without delay. BlueM.MPC implements [[SWMM | SWMM5]] for process modelling and [[BlueM.Opt | BlueM.Opt]] for optimization. | ||
==Model Predictive Control (MPC) of urban drainage systems== | |||
Model predictive control is a method that was first used for process control of chemical plants and oil refineries. MPC is conceptually a method for generating feedback control actions by continuously solving an open-loop optimal control problem over a finite control horizon. MPC systems are characterized by three principles: | |||
1. Implementation of a receding horizon strategy. | |||
2. Explicit use of a process model to predict future state developments of the | |||
system. | |||
3. Application of optimization algorithms to calculate optimal control settings. | |||
For the operation of urban drainage systems only view MPC systems are in operation. Off-line control systems are much more popular. The best known MPC system is the control system of the Quebec Urban Community (QUC) in Canada which is operation since 1999 ({{:Literatur:Pleau-et-al_2005}}). MPC applications of sewer networks are so far not popular since the control constraints (i.e. the available time to calculate control decisions) place restrictions on the degree of sophistication of the process model and the optimization algorithm. In many other technical disciplines MPC is based on linear models. But flow processes in sewer network are highly nonlinear and the proper mathematical description of these processes is based on hyperbolic differential equations. The application of simplified flow routing models is possible but the ability to simulate flows correctly has to be questioned. Further information on MPC applications for urban drainage systems is given in {{:Literatur:Rauch-Harremoes_1999}} and {{:Literatur:Pirsing-et-al_2006}}. | |||
==Application== | ==Application== | ||
See section '''[[BlueM.MPC application]]''' | |||
==Theory== | |||
See section '''[[BlueM.MPC theory]]''' | |||
==Literature== | |||
<references/> | |||
<div class="achtung">'''Note:''' Development of BlueM.MPC has been discontinued!</div> | |||
[[Category:BlueM.MPC]] | |||
Latest revision as of 01:21, 8 April 2018
Description
BlueM.MPC is a software for the simulation of model predictive control (MPC) in sewer networks. MPC is an online strategy for real time control (RTC). Control decisions are calculated during operation with a process model and optimization algorithms. This feature distinguishes MPC from off-line control strategies, in which the control decisions are calculated during the design phase. These control decisions are usually stored in a database (rule-based control) and are available during operation without delay. BlueM.MPC implements SWMM5 for process modelling and BlueM.Opt for optimization.
Model Predictive Control (MPC) of urban drainage systems
Model predictive control is a method that was first used for process control of chemical plants and oil refineries. MPC is conceptually a method for generating feedback control actions by continuously solving an open-loop optimal control problem over a finite control horizon. MPC systems are characterized by three principles:
1. Implementation of a receding horizon strategy.
2. Explicit use of a process model to predict future state developments of the system.
3. Application of optimization algorithms to calculate optimal control settings.
For the operation of urban drainage systems only view MPC systems are in operation. Off-line control systems are much more popular. The best known MPC system is the control system of the Quebec Urban Community (QUC) in Canada which is operation since 1999 (Pleau et al. (2005)[1]). MPC applications of sewer networks are so far not popular since the control constraints (i.e. the available time to calculate control decisions) place restrictions on the degree of sophistication of the process model and the optimization algorithm. In many other technical disciplines MPC is based on linear models. But flow processes in sewer network are highly nonlinear and the proper mathematical description of these processes is based on hyperbolic differential equations. The application of simplified flow routing models is possible but the ability to simulate flows correctly has to be questioned. Further information on MPC applications for urban drainage systems is given in Rauch & Harremoes (1999)[2] and Pirsing et al. (2006)[3].
Application
See section BlueM.MPC application
Theory
See section BlueM.MPC theory
Literature
- ↑ Pleau, M., Colas, H., Lavallee, P., Pelletier, G., and Bonin, R. (2005): Global optimal real-time control of the Quebec urban drainage system. Environmental Modelling & Software, 20(2005), 401-413,
- ↑ Rauch, W., Harremoes, P. (1999): Genetic algorithms in real time control applied to minimize transient pollution from urban wastewater systems. Water Research, 33(5), 1265-1277, 1999.
- ↑ Pirsing, A., Rosen, R., Obst, B., Montrone, F. (2006): Einsatz mathematischer Optimierungsverfahren bei der Abflusssteuerung in Kanalnetzen. GWF (Wasser - Abwasser), 147(5), 376-383, 2006.