New offset-free method for model predictive control of open channels

Abstract

a b s t r a c tIrrigation or drainage canals can be controlled by model predictive control (MPC). Applying MPC with an internal model in the presence of unknown disturbances in some cases can lead to steady state offset. Therefore an additional component should be implemented along with the MPC. A new method eliminating the offset has been developed in this paper for MPC. It is based on combining two basic approaches of MPC. It has been implemented to control water levels in the three-pool UPC laboratory canal and further numerically tested using a test case benchmark proposed by the American Society of Civil Engineers (ASCE). It has been found that the developed offset-free method is able to eliminate the steady-state offset, while taking into account known and unknown disturbances.

A two-layer control architecture for operational management and hydroelectricity production maximization in inland waterways using model predictive control

“…Using a numerical discretization method, this software generates an accurate model of canals based on the solution of the Saint-Venant equations. Indeed, SIC 2 has been and still is extensively used by hydrographical network managers and hydraulic and control engineers to test and validate approaches prior to their implementation on the real system [42][43][44][45][46][47][48][49]. Following this approach, and since access to the real system is not feasible, the effect of real disturbances on a model built in SIC 2 is studied.…”

Optimal salinity and water level control of water courses using Model Predictive Control

“…Operational water management aims to optimize the control of these structures by means of Real Time Control (RTC). Over the past decades, RTC techniques have been used in the field of operational water management to control water volumes and levels, such as feedback controller (Clemmens and Wahlin, 2004;Schuurmans, 1997), feedforward controller (Bautista et al, 2003) or Model Predictive Control (MPC) (Aydin et al, 2016;Delgoda et al, 2016;Horváth et al, 2015;Tian et al, 2017Tian et al, , 2016van Overloop et al, 2014). Over about the past 15 years, water quality control has also been considered.…”

Double-layered nonlinear model predictive control based on Hammerstein–Wiener model with disturbance rejection

“…In Li et al, 34 based on double-layered MPC, the target optimization and feasibility of constrained multiobjective multidegree of freedom were studied. In Horváth et al, 35 the double-layered MPC was researched on the offset-free character with unknown disturbances. In Betti et al, 36 for the infeasible reference problem of constrained systems subject to bounded disturbances, a double-layered robust MPC was proposed based on velocity form model.…”