Adaptive multilevel neuro-fuzzy Model Predictive Control for Drinking Water Networks

This paper presents a constrained Model Predictive Control (MPC) strategy enriched with soft-control techniques as neural networks and fuzzy logic, to incorporate self-tuning capabilities and reliability aspects for drinking water transport network management. The system is a multilevel controller with three hierarchical layers: neural level, fuzzy level, MPC level. Results in the Barcelona Water Network have shown that the quasi-explicit nature of the proposed predictive controller leads to improve the computational time, especially when the complexity of the problem structure can vary while tuning the receding horizons.