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Stochastic model predictive control approaches applied to drinking water networks

Author
Grosso, J.; Velarde, P.; Ocampo-Martinez, C.A.; Maestre, J.; Puig, V.
Type of activity
Journal article
Journal
Optimal control applications and methods
Date of publication
2017-07-01
Volume
38
Number
4
First page
541
Last page
558
DOI
https://doi.org/10.1002/oca.2269 Open in new window
Project funding
Operación Eficiente de Infraestructuras Críticas (ECOCIS)
Repository
http://hdl.handle.net/2117/108961 Open in new window
URL
http://onlinelibrary.wiley.com/doi/10.1002/oca.2269/abstract;jsessionid=2F2EEC0A4D9AD9A748108A45BB28E9EE.f03t03 Open in new window
Abstract
Control of drinking water networks is an arduous task, given their size and the presence of uncertainty in water demand. It is necessary to impose different constraints for ensuring a reliable water supply in the most economic and safe ways. To cope with uncertainty in system disturbances due to the stochastic water demand/consumption and optimize operational costs, this paper proposes three stochastic model predictive control (MPC) approaches, namely, chance-constrained MPC, tree-based MPC, and...
Citation
Grosso, J., Velarde, P., Ocampo-Martinez, C.A., Maestre, J., Puig, V. Stochastic model predictive control approaches applied to drinking water networks. "Optimal control applications and methods", 1 Juliol 2017, vol. 38, núm. 4, p. 541-558.
Keywords
management of water systems, model predictive control, stochastic programming, system disturbances
Group of research
CS2AC-UPC - Supervision, Safety and Automatic Control
SAC - Advanced Control Systems

Participants