Application to a large-scale drinking water network of robust MPC for tracking periodic references

In this paper we propose to apply a novel robust predictive controller for tracking periodic references following a constraint tightening procedure to an uncertain discrete time algebraic-differential linear model of a large scale drinking water network. The system considered has been obtained from the water balance equations of a section of Barcelona's drinking water network taking into account bounded additive perturbations. In this model, we assume that a prediction of the water demand is available and that the prediction error is bounded. The controller guarantees that the perturbed closed loop system converges asymptotically to the optimal reachable periodic trajectory, robust constraint satisfaction and recursive feasibility. To demonstrate the main properties of the controller three different simulation scenarios have been considered.