Abstract
We discuss the problem of controlling an irrigation canal to accommodate fast changes in the canal state in response to events such as offtakes announced with no time lag or sudden weather changes. Our proposed approach comprises a hierarchical controller consisting of two layers with decentralized PI controllers in the lower layer and a centralized MPC-based event-driven controller in the higher layer. By incorporating the hierarchical controller structure we achieve a better performance than with the PI controllers only as currently in use in the real world, while barely increasing the communication requirements and remaining robust to temporary communication link breakdowns as the lower layer can work independently of the higher layer when the links are being restored. The operation of the higher-layer controller relies on controlling the head gate and modifying the settings of the local controllers. This way, an acceleration of water transporting is attained as the controller allows for rapid reactions to the need for more water or less water at a location. Specifically, when there is a sudden need for water, the storage in some of the pools is used to temporarily borrow water. Alternatively, when there is too much water at a location, it can be stored for some time in upstream or downstream pools before the PI controllers manage to remove the water.
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Notes
- 1.
MPC is a model-based control technique that uses predictions of the state and forecasts of the external inputs to determine optimal future control actions for the system. At every step, the control sequence is found through solving an optimization problem in a receding horizon manner. We refer to [4, 12] for a detailed description of MPC.
- 2.
The standard method works by increasing inflow from the head gate at the time when an offtake is announced to provide extra water needed for the additional offtake and letting the PI controllers transport that water through subsequent pools to the offtake point. This method relies on the PI controllers only with the higher-layer controller being absent.
References
Álvarez A, Ridao M, Ramirez D, Sánchez L. Constrained predictive control of an irrigation canal. J Irrig Drain Eng. 2013;139(10):841–854.
Bemporad A, Morari M. Control of systems integrating logic, dynamics, and constraints. Automatica 1999;35(3):407–427.
Bos G. Discharge measurement structures. In: International Institute for Land Reclamation and Improvement, Publication 20. ILRI; 1976.
Camacho EF, Bordons C. Model predictive control. Berlin Heidelberg: Springer; 1999.
Cantoni M, Weyer E, Li Y, Ooi SK, Mareels I, Ryan M. Control of large-scale irrigation networks. In: Proc IEEE. 2007;95(1):75–91.
Chow VT (1959) Open-channel hydraulics. McGraw-Hill civil engineering. London: McGraw-Hill; 1959.
Dahlin EB. Designing and tuning digital controllers. Instrum Control Syst. 1968;41(6):77–83.
De Schutter B, De Moor B. Optimal traffic light control for a single intersection. Eur J Control. 1998;4(3):260–276.
Li Y, Cantoni M (2008) Distributed controller design for open water channels. In: Proceedings of the 17th IFAC World Congress, Seoul; 2008. pp. 10033–10038
Litrico X, Fromion V, Baume J-P, Rijo M. Modelling and PI controller design for an irrigation canal. In: Proceedings of the 2003 European Control Conference, Cambridge; 2003.
Litrico X, Malaterre P-O, Baume J-P, Vion P-Y, Ribot-Bruno J. Automatic tuning of PI controllers for an irrigation canal pool. J Irrig Drain Eng ASCE. 2007;133:27–37.
Maciejowski JM. Predictive control with constraints. Essex: Prentice Hall; 2002.
Malaterre P-O. Control of irrigation canals: why and how? In: Proceedings of the international workshop on numerical modelling of hydrodynamics for water resources, Zaragoza; 2007. pp. 271–293.
Malaterre P-O, Baume JP. Modeling and regulation of irrigation canals: existing applications and ongoing researches. In: Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics, vol. 4, San Diego; 1998. pp 3850–3855.
Negenborn RR, van Overloop P-J, Keviczky T, De Schutter B. Distributed model predictive control for irrigation canals. Netw Heterog Media. 2009;4(2):359–380.
Ooi SK, Weyer E. Control design for an irrigation channel from physical data. Control Eng Pract. 2008;16(9):1132–1150.
Perkins S. Is agriculture sucking fresh water dry? Science NOW, online. Published 13 Feb 2012.
Sadowska A, De Schutter B, van Overloop P-J. Delivery-oriented hierarchical predictive control of an irrigation canal: event-driven versus time-driven approaches. IEEE Trans Control Syst Technol. 2015, doi: 10.1109/TCST.2014.2381600
Sadowska A, van Overloop P-J, Burt C, De Schutter B. Hierarchical operation of water level controllers: formal analysis and application on a large scale irrigation canal. Water Resour Manag. 2014;28(14):4999–5019
Schuurmans J, Clemmens A, Dijkstra S, Hof A, Brouwer R. Modeling of irrigation and drainage canals for controller design. J Irrig Drain Eng. 1999;125(6):338–344.
Schuurmans J, Hof A, Dijkstra S, Bosgra O, Brouwer R. Simple water level controller for irrigation and drainage canals. J Irrig Drain Eng. 1999;125(4):189–195.
Silva P, Botto MA, Figueiredo J, Rijo M. Model predictive control of an experimental water canal. In: Proceedings of the 2007 European Control Conference, Kos; 2007. pp. 2977–2984.
Tian X, Maestre JM, van Overloop PJ, Negenborn RR. Distributed model predictive control for multi-objective water system management. In: Proceedings of the 10th International Conference on Hydroinformatics, Hamburg, July 2012. Paper 175.
van Ekeren H, Negenborn RR, van Overloop PJ, De Schutter B. Hybrid model predictive control using time-instant optimization for the Rhine-Meuse delta. In: Proceedings of the 2011 IEEE International Conference on Networking, Sensing and Control, Barcelona; 2011. pp. 216–221.
van Ekeren H, Negenborn RR, van Overloop PJ, De Schutter B. Time-instant optimization for hybrid model predictive control of the Rhine-Meuse Delta. J. Hydroinformatics. 2013;15(2):271–292.
van Overloop PJ, Clemmens AJ, Strand RJ, Wagemaker RMJ. Real-time implementation of model predictive control on MSIDD’s WM canal. J Irrig Drain Eng ASCE. 2010;136(11): 747–756.
van Overloop PJ, Schuurmans J, Brouwer R, Burt C. Multiple-model optimization of proportional integral controllers on canals. J Irrig Drain Eng ASCE. 2005;131(2):190–196.
Xu M, Negenborn RR, van Overloop PJ, van de Giesen NC. De Saint-Venant equations-based model predictive control of open channel flow. Adv Water Res. 2012;49:37–45.
Ziegler JG, Nichols NB. Optimum Settings for Automatic Controllers. Trans ASME. 1942;64:759–768.
Acknowledgements
Research supported by the European Union Seventh Framework Programme [FP7/2007–2013] under grant agreement no. 257462 HYCON2 Network of Excellence.
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Sadowska, A., van Overloop, P.J., Burt, C., De Schutter, B. (2015). Hierarchical MPC-Based Control of an Irrigation Canal. In: Ocampo-Martinez, C., Negenborn, R. (eds) Transport of Water versus Transport over Water. Operations Research/Computer Science Interfaces Series, vol 58. Springer, Cham. https://doi.org/10.1007/978-3-319-16133-4_10
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