Technical Papers
Apr 15, 2019

Constrained Model Predictive Control Algorithm for Cascaded Irrigation Canals

Publication: Journal of Irrigation and Drainage Engineering
Volume 145, Issue 6

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.

References

Alvarez, A., M. A. Ridao, D. R. Ramirez, and L. Sanchez. 2013. “Constrained predictive control of an irrigation canal.” J. Irrig. Drain. Eng. 139 (10): 841–854. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000619.
Aydin, B. E., P. J. van Overloop, M. Rutten, and X. Tian. 2017. “Offset-free model predictive control of an open water channel based on moving horizon estimation.” J. Irrig. Drain. Eng. 143 (3): B4016005. https://doi.org/10.1061/(ASCE)IR.1943-4774.0001085.
Balogun, O. S., M. Hubbard, and J. J. Devries. 1988. “Automatic-control of canal flow using linear quadratic regulator theory.” J. Hydraul. Eng. 114 (1): 75–102. https://doi.org/10.1061/(ASCE)0733-9429(1988)114:1(75).
Bautista, E., and A. J. Clemmens. 2005. “Volume compensation method for routing irrigation canal demand changes.” J. Irrig. Drain. Eng. 131 (6): 494–503. https://doi.org/10.1061/(ASCE)0733-9437(2005)131:6(494).
Bautista, E., A. J. Clemmens, and T. Strelkoff. 1997. “Comparison of numerical procedures for gate stroking.” J. Irrig. Drain. Eng. 123 (2): 129–136. https://doi.org/10.1061/(ASCE)0733-9437(1997)123:2(129).
Burt, C. M. 2013. “The irrigation sector shift from construction to modernization: What is required for success?” Irrig. Drain. 62 (3): 247–254. https://doi.org/10.1002/ird.1703.
Camacho, E. F., and C. Bordons. 2010. Model predictive control. London: Springer.
Cen, L. H., Z. Q. Wu, X. F. Chen, Y. G. Zou, and S. H. Zhang. 2017. “On modeling and constrained model predictive control of open irrigation canals.” J. Control Sci. Eng. 2017: 1–10. https://doi.org/10.1155/2017/6257074.
Clemmens, A. J., T. F. Kacerek, B. Grawitz, and W. Schuurmans. 1998. “Test cases for canal control algorithms.” J. Irrig. Drain. Eng. 124 (1): 23–30. https://doi.org/10.1061/(ASCE)0733-9437(1998)124:1(23).
Clemmens, A. J., and J. Schuurmans. 2004. “Simple optimal downstream feedback canal controllers: Theory.” J. Irrig. Drain. Eng. 130 (1): 26–34. https://doi.org/10.1061/(ASCE)0733-9437(2004)130:1(26).
Clemmens, A. J., and R. J. Strand. 2010. “Application of software for automatic canal management (SacMan) to the WM lateral canal.” J. Irrig. Drain. Eng. 136 (7): 451–459. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000120.
Clemmens, A. J., R. J. Strand, and E. Bautista. 2010. “Routing demand changes to users on the WM lateral canal with SacMan.” J. Irrig. Drain. Eng. 136 (7): 470–478. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000226.
Cui, W., W. X. Chen, X. P. Mu, and Y. B. L. G. Bai. 2014. “Canal controller for the largest water transfer project in China.” Irrig. Drain. 63 (4): 501-5–511. https://doi.org/10.1002/ird.1817.
Fele, F., J. M. Maestre, S. M. Hashemy, D. M. de la Pena, and E. F. Camacho. 2014. “Coalitional model predictive control of an irrigation canal.” J. Process Control 24 (4): 314–325. https://doi.org/10.1016/j.jprocont.2014.02.005.
Gomez, M., J. Rodellar, and J. A. Mantecon. 2002. “Predictive control method for decentralized operation of irrigation canals.” Appl. Math. Model. 26 (11): 1039–1056. https://doi.org/10.1016/S0307-904X(02)00059-8.
Hashemy, S. M., M. J. Monem, S. Isapoor, and P. J. van Overloop. 2013. “Using in-line reservoir operational strategy to improve Dez Main irrigation canal performance.” Irrig. Drain. 62 (4): 458–467. https://doi.org/10.1002/ird.1741.
Hoogeveen, J., J. M. Faures, L. Peiser, J. Burke, and N. van de Giesen. 2015. “GlobWat: A global water balance model to assess water use in irrigated agriculture.” Hydrol. Earth Syst. Sci. 19 (9): 3829–3844. https://doi.org/10.5194/hess-19-3829-2015.
Horvath, K., E. Galvis, J. Rodellar, and M. G. Valentin. 2014. “Experimental comparison of canal models for control purposes using simulation and laboratory experiments.” J. Hydroinform. 16 (6): 1390–1408. https://doi.org/10.2166/hydro.2014.110.
Horváth, K., E. Galvis, M. G. Valentín, and J. R. Benedé. 2015a. “Is it better to use gate opening as control variable than discharge to control irrigation canals?” J. Irrig. Drain. Eng. 141 (3): 04014054 . https://doi.org/10.1061/(ASCE)IR.1943-4774.0000798.
Horváth, K., E. Galvis, M. G. Valentín, and J. Rodellar. 2015b. “New offset-free method for model predictive control of open channels.” Control Eng. Pract. 41 (2015): 13–25. https://doi.org/10.1016/j.conengprac.2015.04.002.
Isapoor, S., A. Montazar, P. J. van Overloop, and N. van de Giesen. 2011. “Designing and evaluating control systems of the Dez Main Canal.” Irrig. Drain. 60 (1): 70–79. https://doi.org/10.1002/ird.545.
Lozano, D., C. Arranja, M. Rijo, and L. Mateos. 2010. “Simulation of automatic control of an irrigation canal.” Agric. Water Manage. 97 (1): 91–100. https://doi.org/10.1016/j.agwat.2009.08.016.
Malaterre, P. O., D. C. Rogers, and J. Schuurmans. 1998. “Classification of canal control algorithms.” J. Irrig. Drain. Eng. 124 (1): 3–10. https://doi.org/10.1061/(ASCE)0733-9437(1998)124:1(3).
Montazar, A., P. J. van Overloop, and R. Brouwer. 2005. “Centralized controller for the Narmada main canal.” Irrig. Drain. 54 (1): 79–89. https://doi.org/10.1002/ird.155.
Qin, S. J., and T. A. Badgwell. 2003. “A survey of industrial model predictive control technology.” Control Eng. Pract. 11 (7): 733–764. https://doi.org/10.1016/S0967-0661(02)00186-7.
Reddy, J. M., and R. G. Jacquot. 1999. “Stochastic optimal and suboptimal control of irrigation canals.” J. Water Resour. Plan. Manage. 125 (6): 369–378. https://doi.org/10.1061/(ASCE)0733-9496(1999)125:6(369).
Rogers, D. C., and J. Goussard. 1998. “Canal control algorithms currently in use.” J. Irrig. Drain. Eng. 124 (1): 11–15. https://doi.org/10.1061/(ASCE)0733-9437(1998)124:1(11).
Schuurmans, J., O. H. Bosgra, and R. Brouwer. 1995. “Open-channel flow model approximation for controller-design.” Appl. Math. Model. 19 (9): 525–530. https://doi.org/10.1016/0307-904X(95)00053-M.
Schuurmans, J., A. Hof, S. Dijkstra, O. H. Bosgra, and R. Brouwer. 1999. “Simple water level controller for irrigation and drainage canals.” J. Irrig. Drain. Eng. 125 (4): 189–195. https://doi.org/10.1061/(ASCE)0733-9437(1999)125:4(189).
Shahdany, S. M. H., E. A. Majd, A. Firoozfar, and J. M. Maestre. 2016. “Improving operation of a main irrigation canal suffering from inflow fluctuation within a centralized model predictive control system: Case study of Roodasht Canal, Iran.” J. Irrig. Drain. Eng. 142 (11): 05016007. https://doi.org/10.1061/(ASCE)IR.1943-4774.0001087.
Shang, Y. Z., P. Rogers, and G. Q. Wang. 2012. “Design and evaluation of control systems for a real canal.” Sci. China Technol. Sci. 55 (1): 142–154. https://doi.org/10.1007/s11431-011-4620-9.
Tian, X., P. J. van Overloop, R. R. Negenborn, and N. van de Giesen. 2015. “Operational flood control of a low-lying delta system using large time step model predictive control.” Adv. Water Resour. 75: 1–13. https://doi.org/10.1016/j.advwatres.2014.10.010.
van Overloop, P. J., A. J. Clemmens, R. J. Strand, R. M. J. Wagemaker, and E. Bautista. 2010. “Real-time implementation of model predictive control on maricopa-stanfield irrigation and drainage district’s WM canal.” J. Irrig. Drain. Eng. 136 (11): 747–756. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000256.
van Overloop, P.-J., S. Weijs, and S. Dijkstra. 2008. “Multiple model predictive control on a drainage canal system.” Control Eng. Pract. 16 (5): 531-5–540. https://doi.org/10.1016/j.conengprac.2007.06.002.
Wahlin, B. T. 2004. “Performance of model predictive control on ASCE Test Canal 1.” J. Irrig. Drain. Eng. 130 (3): 227–238. https://doi.org/10.1061/(ASCE)0733-9437(2004)130:3(227).
Wahlin, B. T., and A. J. Clemmens. 2002. “Performance of historic downstream canal control algorithms on ASCE Test Canal 1.” J. Irrig. Drain. Eng. 128 (6): 365–375. https://doi.org/10.1061/(ASCE)0733-9437(2002)128:6(365).
Wahlin, B. T., and A. J. Clemmens. 2006. “Automatic downstream water-level feedback control of branching canal networks: Theory.” J. Irrig. Drain. Eng. 132 (3): 198–207. https://doi.org/10.1061/(ASCE)0733-9437(2006)132:3(198).
Wang, Z. J., Z. L. Zheng, G. Y. Xu, and G. Y. Jiang. 2018. “Linear quadratic optimal control of multi-cascaded canals.” [In Chinese.] Adv. Water Sci. 29 (3): 383–389.
Xu, M. 2017. “Model predictive control of an irrigation canal using dynamic target trajectory.” J. Irrig. Drain. Eng. 143 (3): B4016004 . https://doi.org/10.1061/(ASCE)IR.1943-4774.0001084.

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Go to Journal of Irrigation and Drainage Engineering
Journal of Irrigation and Drainage Engineering
Volume 145Issue 6June 2019

History

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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Authors

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Ph.D. Candidate, Dept. of Hydraulic Engineering, Tsinghua Univ., Beijing 100084, China. ORCID: https://orcid.org/0000-0002-1700-0176. Email: [email protected]
Zhongjing Wang [email protected]
Professor, Dept. of Hydraulic Engineering, Tsinghua Univ., Beijing 100084, China; Professor, State Key Laboratory of Hydroscience and Engineering, Tsinghua Univ., Beijing 100084, China; Professor, State Key Laboratory of Plateau Ecology and Agriculture, Qinghai Univ., Xining 810016, China (corresponding author). Email: [email protected]
Jianshi Zhao, Aff.M.ASCE [email protected]
Associate Professor, Dept. of Hydraulic Engineering, Tsinghua Univ., Beijing 100084, China; Associate Professor, State Key Laboratory of Hydroscience and Engineering, Tsinghua Univ., Beijing 100084, China. Email: [email protected]
Associate Professor, School of Environment and Civil Engineering, Dongguan Univ. of Technology, Dongguan 523106, China. Email: [email protected]

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