Model Predictive Control on Open Water Systems


Van Overloop, P.J.

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Delft University Press


In the research Model Predictive Control on Open Water Systems, the relatively
new control methodology Model Predictive Control is configured for application of
water quantity control on open water systems, especially on irrigation canals and
large drainage systems. The methodology applies an internal model of the open
water system, by which optimal control actions are calculated over a prediction
horizon. As internal model, two simplified models are used, the Integrator Delay
model and the Saint Venant model. Kalman filtering is applied to initialize the
internal models. The optimization uses an objective function in which conflicting
objectives can be weighed. In most of the cases, these conflicting objectives are
keeping the water levels at different locations in the water system within a range
around setpoint and executing this by using as little control effort or energy as
possible. To tune the weight factors in the objective function, an estimate of the
maximum allowed value of each variable in the objective function is used. The
optimization takes the constraints of the control structures into account. Every
control time step, the optimal control actions are calculated, while only the first set
of control actions is actually executed. This results in a controlled water system
that is constantly maintaining the objective in an optimal way, while taking
predictions, such as expected irrigation demands or extreme storm events and
the constraints of the water system into account.