Reference
J. M. Maestre, L. Raso,
P. J. van Overloop, and B. De Schutter,
"Distributed tree-based model predictive control on a drainage water system,"
Journal of Hydroinformatics, vol. 15, no. 2, pp.
335-347, 2013.
Abstract
Open water systems are one of the most externally influenced systems due to
their size and continuous exposure to uncertain meteorological forces. The
control of systems under uncertainty is in general a challenging problem. In
this paper we use a stochastic programming approach to control a drainage
system in which the weather forecast is modeled as a disturbance tree. Each
branch of the tree corresponds to a possible disturbance realization and has a
certain probability associated to it. A model predictive controller is used to
optimize the expected value of the system variables taking into account the
disturbance tree. This technique, tree-based model predictive control (TBMPC),
is solved in a distributed fashion. In particular, we apply dual decomposition
to get an optimization problem that can be solved by different agents in
parallel. In addition, different possibilities are considered in order to
reduce the communicational burden of the distributed algorithm without reducing
the performance of the controller significantly. Finally, the performance of
this technique is compared with others such as minmax or multiple model
predictive control.
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BibTeX
@article{MaeRas:12-018,
author = {Maestre, Jos{\'{e}} M. and Raso, Luciano and van Overloop, Peter
Jules and De Schutter, Bart},
title = {Distributed Tree-Based Model Predictive Control on a Drainage
Water System},
journal = {Journal of Hydroinformatics},
volume = {15},
number = {2},
pages = {335--347},
year = {2013}
}