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Chance-constrained model predictive control for drinking water networks

Author
Grosso, J.M.; Ocampo-Martinez, C.A.; Puig, V.; Joseph, B.
Type of activity
Journal article
Journal
Journal of process control
Date of publication
2014-05-01
Volume
24
Number
5
First page
504
Last page
516
DOI
https://doi.org/10.1016/j.jprocont.2014.01.010 Open in new window
Project funding
Sistemes avançats de control
Repository
http://hdl.handle.net/2117/23369 Open in new window
URL
http://www.sciencedirect.com/science/article/pii/S0959152414000341 Open in new window
Abstract
This paper addresses a chance-constrained model predictive control (CC-MPC) strategy for the management of drinking water networks (DWNs) based on a finite horizon stochastic optimisation problem with joint probabilistic (chance) constraints. In this approach, water demands are considered additive stochastic disturbances with non-stationary uncertainty description, unbounded support and known (or approximated) quasi-concave probabilistic distribution. A deterministic equivalent of the stochastic...
Citation
Grosso, J.M. [et al.]. Chance-constrained model predictive control for drinking water networks. "Journal of process control", 01 Maig 2014, vol. 24, núm. 5, p. 504-516.
Keywords
Chance constraints, Drinking water networks, MPC, Reliability, Robustness
Group of research
CS2AC-UPC - Supervision, Safety and Automatic Control
SAC - Advanced Control Systems

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