PILOTE: Linear Quadratic Optimal Controller for Irrigation Canals

Abstract

Linear quadratic optimal control theory is applied to the automatic control of two different eight-pool irrigation canals. The model used to design the controller is derived from the Saint-Venant equations discretized through the Preissmann implicit scheme. The linear quadratic closed-loop optimal controller is obtained from steady-state solution of the matrix Riccati equation. A Kalman filter reconstructs the state variables and the unknown perturbations from a reduced number of measured variables. Both perturbation rejection and tracking aspects are incorporated in the controller. Known offtake withdrawals and future targets are anticipated through an open-loop scheme utilizing time varying solutions of the linear quadratic optimization problem. The controller and Kalman filter are tested on a full nonlinear model and prove to be stable, robust, and precise.