Abstract
Agricultural irrigation accounts for the largest proportion of freshwater use worldwide, and canal automation potentially improves conveyance efficiency in irrigation canal systems. In this paper, model predictive control (MPC) for a cascaded irrigation canal system was formulated using the integrator-delay model. Magnitude and variation amplitude constraints on input and output imposed on the canal operation were identified along with proposed handling methods, and optimal control actions were achieved by quadratic objective function optimization. The MPC, as well as classical proportional-integral (PI) and centralized linear quadratic (LQ) for comparison, were developed for the Changma South Irrigation District cascaded irrigation canals in Gansu Province (China) and numerically tested via SOBEK software. In contrast to the poor performance of PI and LQ in controlling the studied canal, the results show that MPC can efficiently control the canal system under known demand changes and maintain water levels at control points within the operating range. The control performance improves if normal input and output constraints are incorporated in optimization. However, deadband constraints, which is the minimum variation amplitude of input, cause controlled water levels to oscillate around the reference value and degrade the control performance. In summary, MPC can cope with time delays, coupling effects, and constraints inherent in a cascaded irrigation canals system. Furthermore, it is suggested to evaluate more advanced methods for handling the output and deadband constraints in future studies.
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Acknowledgments
This research was financially supported by the National Key R&D Program of China (Nos. 2016YFC0402900 and 2016YFC0402902), the Science & Technology Project of Qinghai Province (No. 2017-SF-116), and the National Natural Science Foundation of China (No. 41671020). The authors would like to thank the editors and anonymous reviewers for their time and effort in reviewing this manuscript, thanks for their valuable comments and language polishing that helped us improve the manuscript.
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©2019 American Society of Civil Engineers.
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Received: Jul 13, 2018
Accepted: Jan 2, 2019
Published online: Apr 15, 2019
Published in print: Jun 1, 2019
Discussion open until: Sep 15, 2019
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