Developing accurate soft computing methods for groundwater level (GWL) forecasting is
essential for enhancing the planning and management of water resources. Over the past two …

This paper addresses a non-linear economic model predictive control (EMPC) strategy for
water distribution networks (WDNs). A WDN could be considered as a non-linear system …

This study focuses on developing a stochastic model predictive control (MPC) strategy
based on Gaussian processes (GPs) for propagating system disturbances in a receding …

Smart control in water systems aims to reduce the cost of infrastructure expansion by better
utilizing the available capacity through real-time control. The recent availability of sensors …

The design of distributed optimization-based controllers for large-scale systems (LSSs)
implies every time new challenges. The fact that LSSs are generally located throughout …

Despite the proven advantages of scenario-based stochastic model predictive control for the
operational control of water networks, its applicability is limited by its considerable …

Optimizing pump operations is a challenging task for real-time management of water
distribution systems (WDS). With suitable pump scheduling, pumping costs can be …

This paper addresses a novel economic model predictive control (MPC) formulation based
on a periodicity constraint to achieve an optimal periodic operation for discrete-time linear …

Abstract Model predictive control (MPC) is a suitable strategy for the control of large-scale
systems that have multiple design requirements, eg, multiple physical and operational …

This paper presents the application of an economic model predictive control (MPC) for the
operational management of water distribution networks (WDNs) with periodic operation and …