Economic Health-aware MPC-LPV Based on DBN Reliability Model for Water Transport Network.

This paper proposes an economic health-aware model predictive control (MPC) for Drinking Water Transport Networks (DWN) that includes an additional goal to extend the components and system reliability evaluated using a Bayesian Network. The components and system reliability are incorporated in the MPC model using the LPV approach. The MPC controller uses additionally an economic objective function that determines the optimal filling/emptying sequence of the tanks considering that electricity price varies between day and night. The proposed LPV-MPC control approach allows the controller to accommodate the parameter changes. By computing an estimation of the state variables during prediction, the MPC model can be modified considering the estimated state evolution at each time instant. Moreover, the solution of the optimization problem associated with the MPC problem is achieved by solving a series of Quadratic Programs (QP) at each sampling time. This iterative approach reduces the computational load compared to the solution of a non-linear optimization problem. A part of a real drinking water transport network of Barcelona is used as a case study for illustrating the performance of the proposed approach.