Publication
Model predictive control of urban drainage systems considering uncertainty
Journal Article (2023)
Journal
IEEE Transactions on Control Systems Technology
Pages
2968-2975
Volume
31
Number
6
Doc link
https://doi.org/10.1109/TCST.2023.3286648
File
Authors
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Svensen, Jan Lorenz
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Sun, Congcong
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Cembrano Gennari, Gabriela
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Puig Cayuela, Vicenç
Projects associated
Abstract
This paper presents the application of model predictive control (MPC) to address the combined sewer overflow (CSO) problem in urban drainage systems (UDSs) with uncertainty. In UDS, dealing with uncertainty in rain forecast and dynamic models is crucial due to the possible impact on the UDS control performance. Two different MPC approaches are considered: tube-based MPC (T-MPC) and chance-constrained MPC (CC-MPC), which represent uncertainty in deterministic and stochastic manners, respectively. This brief presents how to apply T-MPC to UDS, by establishing a mathematical relation with CC-MPC, and a rigorous mathematical comparison. Based on simulations using the Astlingen benchmark UDS, the strengths and weaknesses of the performance of T-MPC and CC-MPC in UDS were compared. Differences in the involved mathematical computations have also been analyzed. Moreover, the comparison in performance also indicates the applicability of each MPC approach in different uncertainty scenarios
Categories
optimisation, predictive control.
Author keywords
Predictive control, uncertainty, urban drainage
Scientific reference
J.L. Svensen, C. Sun, G. Cembrano and V. Puig. Model predictive control of urban drainage systems considering uncertainty. IEEE Transactions on Control Systems Technology, 31(6): 2968-2975, 2023.
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