Smart Tuning of Predictive Controllers for Drinking Water Networked Systems
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Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2099.1/16319
Tipus de documentProjecte Final de Màster Oficial
Data2010-09
Condicions d'accésAccés obert
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continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
This thesis affords the tuning of a multi-objective predictive controller, particularly designed for
the Barcelona’s drinking water network. Predictive controller objectives have been established
taking into account the minimisation of three criteria; the first one considers economic costs
involved in the distribution process; second one takes into account tank’s safety volumes; and
the third penalises excessive variations in control actions.
Disturbances usually affect the operational conditions in which an automatic control strategy
evolves along time. In the drinking water network (DWN) predictive control strategy, consumer
demands have been modelled as measured disturbances. It is primordial to ensure an effective
rejection of those measured disturbances, respecting to the controller objectives.
Through this thesis, functionalities of the DWN system are illustrated as well as the predictive
control strategy used to solve the multi-objective optimisation problem; later, methods to explore
the space of non-dominated solutions, known as Pareto front, are exposed and a strategy to
choose, at every sample time, a solution in line with the problem objectives. Next, a tuning
strategy, which avoid the Pareto front calculation in the on-line implementation by using a model
that allows to variate the weighting factors of each objective function, in terms of consumer
water demands.
Keywords: Model predictive control, large-scale systems, drinking water networks, multiobjective
optimisation.
Col·leccions
Fitxers | Descripció | Mida | Format | Visualitza |
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Tesis Rodrigo Toro.pdf | Report | 1,860Mb | Visualitza/Obre |