Abstract
Predictive control is one of the most commonly used control methods in a variety of application areas, including hydraulic processes such as water distribution canals for irrigation. This article presents the design and application of predictive control for the water discharge entering into an irrigation canal located in Spain. First, a discrete time linear model of the process is described and its parameters are experimentally identified. The model is well validated within the usual canal operating range and is used to formulate a predictive control law with an incremental formulation. Finally, experimental and simulation results are presented in which predictive control has shown better performance than a well-tuned proportional, integral and derivative controller to automatically manage demanded water discharges.
Highlights
Agriculture consumes between 75 % an 80 % of the world’s freshwater resources, its availability is constantly decreasing and its use will probably be a source of important conflicts
The step experiments were performed with a sampling time of 1 s, measuring and recording both the input gate position and the output water discharge in the commercial programmable logic controller Siemens S7–300 available in the canal facility
The high percentage of validation for the discrete time model (8) shown in (9) suggests that there are not significant dynamics of the process hidden in the perturbation signal Δ(k), and the errors shown in Fig. 5 can be reasonably attributed to the parameter variability of the process around the operation point as well as to the measurement noise
Summary
Agriculture consumes between 75 % an 80 % of the world’s freshwater resources, its availability is constantly decreasing and its use will probably be a source of important conflicts For this reason the modern, efficient and sustainable management of the hydrologic resources is crucial. The control policies in the large distributor canals can be classified as follows: (i) according to the controlled variable, discharge or water level control; (ii) according to the control action variables, discharge or gate opening; and (iii) according to the location of the controlled variable, upstream control or downstream control (Malaterre et al 1998) Though these processes are mainly non-linear and have large time delays, their dynamic behaviour can locally be approximated with linear equations containing timedependent parameters. Calculation is repeated while the prediction horizon is shifted one step forward (Martín Sánchez and Rodellar 2014)
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