Abstract
Model predictive control (MPC) has been extensively studied for controlling irrigation canals. Most of the studies use lumped models and fixed target for the controller. This setup works fine if the water delivery is on demand. However, in the case of on-supply delivery, balancing mismatches between demand and supply and spreading mismatches among all users are crucial. A fixed control target will not meet the request due to the mismatches. In this paper, a dynamic target trajectory approach is proposed to calculate changes of control targets that are used by MPC. The dynamic target trajectory calculates the percentage change of each setpoint based on the total volume mismatch spreading over the available capacity in each canal pool. The approach is applied to the Central Main Canal in Arizona. The results demonstrate that the dynamic trajectory can help the optimization find the optimum more quickly and facilitate tuning of the controller. Moreover, the mismatches can be better distributed over canal pools.
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Acknowledgments
This research was supervised by Dr. Peter-Jules van Overloop (1969–2015) from Delft University of Technology, the Netherlands, and was denoted to memorialize his contributions in the field of canal automation.
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© 2016 American Society of Civil Engineers.
History
Received: Jul 20, 2015
Accepted: Apr 18, 2016
Published online: Jul 12, 2016
Discussion open until: Dec 12, 2016
Published in print: Mar 1, 2017
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