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

Download the digital copy of the doc pdf document

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.