Application of distributed model predictive control to a water delivery canal

Water delivery canals are large, spatially distributed structures whose objective is to bring in a continuous way water from the sources to the points were it is used. Due to their large scale character, the backbone of water delivery canals modeling is made of partial differential equations, in particular the Saint-Venant equations that embody mass and moment conservation. As a consequence this type of plants have an infinite dimension and are difficult to control due to phenomena like wave formation and a strong interaction between different parts. In this work, a canal made of four sequential pools is considered, the gates between adjacent pools being the actuators. In order to tackle the above dynamic characteristics, in particular the strong interaction between canal subsystems, a distributed model predictive control (MPC) algorithm is used. As such, the controllers driving each gate communicate with each other in order to make coordinate moves. The resulting algorithm is a sub-optimal version of a centralized, multivariable, MPC controller. The paper presents the distributed MPC algorithm applied to the canal and shows that it is a near optimum approximation.