Name
Abstract | ||
|---|---|---|
Open water systems are one of the most externally influenced systems due to their size and continuous exposure to uncertain meteorological forces. In this paper we use a stochastic programming approach to control a drainage system in which the weather forecast is modeled as a disturbance tree. A model predictive controller is used to optimize the expected value of the system variables taking into account the disturbance tree. This technique, tree-based model predictive control (TBMPC), is solved in a parallel fashion by means of dual decomposition. In addition, different possibilities are explored to reduce the communicational burden of the parallel algorithm. Finally, the performance of this technique is compared with others such as minmax or multiple model predictive control. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ACC.2012.6314903 | American Control Conference |
Keywords | Field | DocType |
distributed control,predictive control,stochastic programming,trees (mathematics),water supply,weather forecasting,TBMPC,distributed tree-based model predictive control,disturbance tree,drainage system,dual decomposition,open water system,parallel algorithm,stochastic programming approach,uncertain meteorological forces,weather forecast | Control theory,Minimax,Computer science,Control theory,Parallel algorithm,Model predictive control,Expected value,Weather forecasting,Stochastic programming,Trajectory | Conference |
ISSN | ISBN | Citations |
0743-1619 E-ISBN : 978-1-4673-2102-0 | 978-1-4673-2102-0 | 1 |
PageRank | References | Authors |
0.38 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jose Maria Maestre | 1 | 32 | 14.98 |
| Raso, L. | 2 | 1 | 0.38 |
| van Overloop, P.-J. | 3 | 10 | 3.47 |
| Hans Hellendoorn | 4 | 1673 | 220.44 |