Water Resources Management

, Volume 28, Issue 14, pp 4999–5019 | Cite as

Hierarchical Operation of Water Level Controllers: Formal Analysis and Application on a Large Scale Irrigation Canal

  • A. Sadowska
  • P.-J. van Overloop
  • C. Burt
  • B. De Schutter


We introduce a hierachical controller, the purpose of which is to speed up the water delivery process as compared to the standard method applied currently in the field. The lower layer of the hierarchical control consists of local proportional integral filter controllers (PIF controllers) for upstream control at each gate; specifically they are proportional integral controllers with a low-pass filter. In contrast, the higher layer is composed of a centralized model-based predictive controller, which acts by controlling the head gate and by coordinating the local PIF controllers by modifying their setpoints when needed. The centralized controller is event-driven and is invoked only when there is a need for it (a water delivery request) and as such it contributes scarcely to the communication burden. The scheme is robust to temporary communication losses as the local PIF controllers are fully able to control the canal in their normal independent automatic upstream control mode until the communication links are restored. We discuss the application of the hierarchical controller to a precise numerical model of the Central California Irrigation District Main Canal. This shows the improved performance of the new hierarchical controller over the standard control method.


Model predictive control Hierarchical control Irrigation canals 



Research supported by the European Union Seventh Framework Programme [FP7/2007-2013] under grant agreement no. 257462 HYCON2 Network of Excellence and by the California State University Agricultural Research Initiative.


  1. Álvarez A, Ridao M, Ramirez D, Sánchez L (2013) Constrained predictive control of an irrigation canal. J Irrig Drain Eng 139(10):841–854CrossRefGoogle Scholar
  2. Åstrȯm KJ, Hȧgglund T (1995) PID controllers: theory, design, and tuning. Instrument Society of America, Research Triangle Park, NCGoogle Scholar
  3. Burt C, Piao X (2003) Gate modeling results and control algorithm for the central california irrigation district main canal. Tech. rep. Irrigation Training and Research Center, California Polytechnic State UniversityGoogle Scholar
  4. Burt C, Stoddard R, Landon R, White C, Freeman B (2005) Canal modernization in central california irrigation district – case study. In: Proceedings of the 2005 USCID conference on SCADA and related Technologies for irrigation district modernization, Vancouver, WA, pp 235–246Google Scholar
  5. Camacho E, Bordons C (1999) Model predictive control. Springer, Berlin HeidelbergCrossRefGoogle Scholar
  6. Cantoni M, Weyer E, Li Y, Ooi SK, Mareels I, Ryan M (2007) Control of large-scale irrigation networks. Proc IEEE 95(1):75–91CrossRefGoogle Scholar
  7. CCID (2013) History of CCID.
  8. Chow VT (1959) Open-channel hydraulics. McGraw-Hill Civil Engineering, LondonGoogle Scholar
  9. Cristea S, de Prada C, Sarabia D, Gutiérrez G (2011) Aeration control of a wastewater treatment plant using hybrid NMPC. Comput Chem Eng 35(4):638–650CrossRefGoogle Scholar
  10. De Schutter B, De Moor B (1998) Optimal traffic light control for a single intersection. Eur J Control 4(3):260–276CrossRefGoogle Scholar
  11. van Ekeren H, Negenborn RR, van Overloop PJ, De Schutter B (2011) 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, pp 216–221Google Scholar
  12. Garey MR, Johnson DS (1979) Computers and intractability: a guide to the theory of NP-completeness, 1st edn. W. H. Freeman & Co., New YorkGoogle Scholar
  13. Hooke R, Jeeves TA (1961) direct search solution of numerical and statistical problems. J ACM 8(2):212–229CrossRefGoogle Scholar
  14. ITRC (2001) Technical manual of canal CAD v. 2.05. ITRC, USAGoogle Scholar
  15. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220(4598):671–680CrossRefGoogle Scholar
  16. Lemos JM, Machado F, Nogueira N, Rato L, Rijo M (2009) Adaptive and non-adaptive model predictive control of an irrigation channel. Netw Heterogenous Med 4(2):303–324CrossRefGoogle Scholar
  17. Li Y, Cantoni M (2008) Distributed controller design for open water channels. In: Proceedings of the 17th IFAC world congress, Seoul. pp 10,033–10,038Google Scholar
  18. Li Y, De Schutter B (2010) Performance analysis of irrigation channels with distributed control. In: Proceedings of the 2010 IEEE international conference on control applications, Yokohama. pp 2148–2153Google Scholar
  19. Li Y, De Schutter B (2012) Control of a string of identical pools using non-identical feedback controllers. IEEE Trans Control Syst Technol 20(6):1638–1646CrossRefGoogle Scholar
  20. Litrico X, Fromion V, Baume JP, Rijo M (2003) Modelling and PI controller design for an irrigation canal. In: Proceedings of the 2003 european control conference, CambridgeGoogle Scholar
  21. Litrico X, Malaterre PO, Baume JP, Vion P, Ribot-Bruno J (2007) Automatic tuning of PI controllers for an irrigation canal pool. J Irrig Drain Eng -ASCE 133:27–37CrossRefGoogle Scholar
  22. Maciejowski JM (2002) Predictive control with constraints. Prentice Hall, EnglandGoogle Scholar
  23. Maestre JM, Muoz de la Pea D, Camacho EF (2011) Distributed model predictive control based on a cooperative game. Optim Control Appl Methods 32(2):153–176CrossRefGoogle Scholar
  24. Malaterre P, Rogers D, Schuurmans J (1998) Classification of canal control algorithms. J Irrig Drain Eng 124(1):3–10CrossRefGoogle Scholar
  25. Malaterre PO (2007) Control of irrigation canals: why and how? In: Proceedings of the international workshop on numerical modelling of hydrodynamics for water resources, Zaragoza. pp 271–293Google Scholar
  26. Malaterre PO, Baume JP (1998) Modeling and regulation of irrigation canals: existing applications and ongoing researches. In: Proceedings of the 1998 IEEE international conference on systems, man, and cybernetics, San Diego, vol 4. pp 3850–3855Google Scholar
  27. Malaterre PO, Baume JP (1999) Optimum choice of control action variables and linked algorithms. comparison of different alternatives. In: Proceedings of the workshop on modernization of irrigation water delivery systems, Phoenix. pp 387–406Google Scholar
  28. Mitchell M (1996) An introduction to genetic algorithms. MIT Press, CambridgeGoogle Scholar
  29. Negenborn RR, van Overloop PJ, Keviczky T, De Schutter B (2009) Distributed model predictive control for irrigation canals. Netw Heterogeneous Med 4(2):359–380CrossRefGoogle Scholar
  30. Ooi SK, Weyer E (2008) Control design for an irrigation channel from physical data. Control Eng Pract 16(9):1132–1150CrossRefGoogle Scholar
  31. Oppenheim AV, Willsky AS, Nawab SH (1996) Signals syst, 2nd. Prentice-Hall, Inc., Upper Saddle River, NJ, USAGoogle Scholar
  32. van Overloop PJ (2006) Model predictive control on open water systems. PhD thesis. Delft University of Technology, The NetherlandsGoogle Scholar
  33. van Overloop PJ, Schuurmans J, Brouwer R, Burt C (2005) Multiple-model optimization of proportional integral controllers on canals. J Irrig Drain Eng - ASCE 131(2):190–196CrossRefGoogle Scholar
  34. van Overloop PJ, Clemmens A, Strand R, Wagemaker R (2010) Real-time implementation of model predictive control on MSIDD’s WM canal. J Irrig Drain Eng - ASCE 136(11):747–756CrossRefGoogle Scholar
  35. Richardson D (2008) If you can’t raise the river, modernize the canal. Pacific Standard:6Google Scholar
  36. Sadowska A, De Schutter B, van Overloop PJ (2013a) Delivery-oriented hierarchical predictive control of an irrigation canal: event-driven versus time-driven approaches. submittedGoogle Scholar
  37. Sadowska A, De Schutter B, van Overloop PJ (2013b) Event-driven hierarchical control of irrigation canals. In: Proceedings of the 7th international conference on irrigation and drainage, USCID, Phoenix. pp 457–472Google Scholar
  38. Schuurmans J (1997) Control of water levels in open-channels. PhD thesis. Delft University of Technology, The NetherlandsGoogle Scholar
  39. Schuurmans J, Clemmens A, Dijkstra S, Hof A, Brouwer R (1999) Modeling of irrigation and drainage canals for controller design. J Irrig Drain Eng 125(6):338–344CrossRefGoogle Scholar
  40. Silva P, Botto MA, Figueiredo J, Rijo M (2007) Model predictive control of an experimental water canal. In: Proceedings of the 2007 european control conference, Kos. pp 2977–2984Google Scholar
  41. Torczon V (1997) On the convergence of pattern search algorithms. SIAM J Optim 7(1):1–25CrossRefGoogle Scholar
  42. Weyer E (2008) Control of irrigation channels. IEEE Trans Control Syst Technol 16(4):664–675CrossRefGoogle Scholar
  43. Xu M, Schwanenberg D (2012) Comparison of sequential and simultaneous model predictive control of reservoir systems. In: Proceedings of the 10th international conference on hydroinformatics, Hamburg. pp 2148–2153Google Scholar
  44. Xu M, Negenborn R, van Overloop P, van de Giesen N (2012) De Saint-Venant equations-based model predictive control of open channel flow. Adv Water Resour 37–45:37–45CrossRefGoogle Scholar
  45. Zafra-Cabeza A, Maestre JM, Ridao MA, Camacho EF, Sȧnchez L (2011) Hierarchical distributed model predictive control for risk mitigation: An irrigation canal case study. In: Proceedings of the 2011 american control conference, San Francisco. 3172–3177Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • A. Sadowska
    • 1
  • P.-J. van Overloop
    • 2
  • C. Burt
    • 3
  • B. De Schutter
    • 1
  1. 1.Delft Center for Systems and ControlDelft University of TechnologyDelftThe Netherlands
  2. 2.Water Resources ManagementDelft University of TechnologyDelftThe Netherlands
  3. 3.Irrigation Training and Research Center (ITRC)California Polytechnic State UniversitySan Luis ObispoUSA

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