A Model Predictive Water-Level Difference Control Method for Automatic Control of Irrigation Canals

Abstract

In this paper, automatic control of the water level in an irrigation canal by automatic regulation of intermediate gates was studied. Previous scholars have proposed a water level difference control strategy that works to keep relative deviations in all pools the same for a particular situation where the operator does not have full control over the canal inflow, with the centralized linear quadratic regulator (LQR) control method used. While in practice, the deviation tolerance of pools may differ in some canals which limits the applicability of the control strategy. In this work, a weight coefficient was added to the deviation and the algorithm was improved to keep the relative deviations to certain proportions. The model predictive control (MPC) method was then used with this improved control strategy and was compared to the LQR control method using the same control strategy. The results showed that the improved strategy can keep the water level deviations in all pools to certain proportions, as is our objective. Also, under this difference control strategy, the MPC method greatly improved the control performance compared to the LQR control method.

Automatic Control of the Middle Route Project for South-to-North Water Transfer Based on Linear Model Predictive Control Algorithm

“…Equations (14) and (15) are the control models in the form of state space equations for a single pool. The state space equations for a multi-pool canal can also be written in the form of Equations (14) and (15).…”

“…The MPC strategy explicitly uses a simplified process model of the real system to determine control actions by minimizing an objective function. The aforementioned simplified control model with Equations (14) and (15) can be used as the process model. An output prediction is given by the process model.…”

“…With Equations (14) and (15), the prediction for the output vector two time steps into the future is…”

“…The MIMO control algorithm is also called a centralized control algorithm, and typically uses linear quadratic optimal control [11] or model predictive control (MPC). As MPC can deal with various constraint problems and foreseen delivery problems, it is well-suited to real-time automatic control of canal irrigation systems with more complicated working conditions [12][13][14].…”

A Simple Method for the Control Time of a Pumping Station to Ensure a Stable Water Level Immediately Upstream of the Pumping Station under a Change of the Discharge in an Open Channel

“…Wahlin et al [27] found that combined feedforward-feedback controllers were better than either feedforward or feedback controllers alone. Kong et al [28] added a deviation weight coefficient into the algorithm for the middle route of the South-to-North Water Diversion Project, which could keep the water level deviations in all pools to certain proportions. However, these automatic control algorithms are incapable of dealing with the switching of working conditions and are rarely used in pumping stations.…”