Reference
R. R. Negenborn, P.-J. van Overloop, T.
Keviczky, and B. De Schutter, "Distributed model predictive control of
irrigation canals,"
Networks and Heterogeneous Media,
vol. 4, no. 2, pp. 359-380, June 2009.
Abstract
Irrigation canals are large-scale systems, consisting of many interacting
components, and spanning vast geographical areas. For safe and efficient
operation of these canals, maintaining the levels of the water flows close to
pre-specified reference values is crucial, both under normal operating
conditions as well as in extreme situations. Irrigation canals are equipped
with local controllers, to control the flow of water by adjusting the settings
of control structures such as gates and pumps. Traditionally, the local
controllers operate in a decentralized way in the sense that they use local
information only, that they are not explicitly aware of the presence of other
controllers or subsystems, and that no communication among them takes place.
Hence, an obvious drawback of such a decentralized control scheme is that
adequate performance at a system-wide level may be jeopardized, due to the
unexpected and unanticipated interactions among the subsystems and the actions
of the local controllers. In this paper we survey the state-of-the-art
literature on distributed control of water systems in general, and irrigation
canals in particular. We focus on the model predictive control (MPC) strategy,
which is a model-based control strategy in which prediction models are used in
an optimization to determine optimal control inputs over a given horizon. We
discuss how communication among local MPC controllers can be included to
improve the performance of the overall system. We present a distributed control
scheme in which each controller employs MPC to determine those actions that
maintain water levels after disturbances close to pre-specified reference
values. Using the presented scheme the local controllers cooperatively strive
for obtaining the best system-wide performance. A simulation study on an
irrigation canal with seven reaches illustrates the potential of the approach.
Publisher page
Downloads
BibTeX
@article{Negvan:08-032,
author = {Negenborn, Rudi R. and van Overloop, Peter-Jules and Keviczky,
Tam{\'a}s and De Schutter, Bart},
title = {Distributed Model Predictive Control of Irrigation Canals},
journal = {Networks and Heterogeneous Media},
volume = {4},
number = {2},
pages = {359--380},
month = jun,
year = {2009}
}