Water demand forecasting for the optimal operation of large-scale drinking water networks: The Barcelona Case Study

Conference:  19th World Congress of the International Federation of Automatic Control. Cape Town, South Africa. 24-29 August, 2014. Authors: A.K. Sampathirao, J.-M. Gross, P. Sopasakis, C. Ocampo-Matrinez, A. Bemporad and V. Puig Abstract: Drinking Water Networks (DWN) are large-scale multiple-input multiple-output systems with uncertain disturbances (such as the water demand from the consumers) and involve components of linear,

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Journal of Process Control article on Chance-constrained model predictive control for drinking water networks

Journal of Process Control (2014) January 14, 2014 Authors: J.M. Grosso, , C. Ocampo-Martínez, V. Puig, B. Joseph 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

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Learning-Based Tuning of Supervisory Model Predictive Control for Drinking Water Networks

Publication journal: Engineering Applications of Artificial Intelligence. Volume 26, Issue 7, August 2013, Pages 1741–1750 Authors:  J.M. Grosso , C. Ocampo-Martínez, V. Puig This paper presents a constrained Model Predictive Control (MPC) strategy enriched with soft-control techniques as neural networks and fuzzy logic, to incorporate self-tuning capabilities and reliability aspects for the management of drinking water networks (DWNs). The

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