Technical Papers
Jan 16, 2013

Flood Control with Model Predictive Control for River Systems with Water Reservoirs

Publication: Journal of Irrigation and Drainage Engineering
Volume 139, Issue 7

Abstract

Many control strategies can be found in the literature for controlling river systems. One of these methods is model predictive control (MPC), and it has already shown its efficiency for set-point control of reaches and irrigation channels. This paper shows that MPC can also be used for flood control of river systems. The proposed controllers use the buffer capacity of water reservoirs in an optimal way when there is a risk of flooding, and they recover the used buffer capacity as fast as possible. The performance of the controllers is tested on a river system consisting of multiple channels, gates, and a water reservoir. One controller is used in combination with a Kalman filter, which estimates all the states of the river system on the basis of a very limited number of measured water levels. It was observed that the influence of this estimator on the control performance was minimal.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

The authors would like to thank the reviewers of this manuscript for their suggestions and remarks that undoubtedly contributed to the improvement of our initial submission.
Research was supported by Research Council KUL: GOA/10/09 MaNet, PFV/10/002 (OPTEC), FWO: Ph.D./postdoctoral grants and projects: G.0320.08 (convex MPC), G.0558.08 (Robust MHE), Belgian Federal Science Policy Office: IUAP P7/ (DYSCO, Dynamical systems, control and optimization, 2012-2017).

References

Barjas Blanco, T., Willems, P., Chiang, P. P.-K., Haverbeke, N., Berlamont, J., and De Moor, B. (2010). “Flood regulation using nonlinear model predictive control.” Control Eng. Pract., 18(10), 1147–1157.
Breckpot, M., Agudelo, O. M., De Moor, B. (2012a). “Control of a single reach with model predictive control.” River Flow 2012, Proc., Int. Conf. on Fluvial Hydraulics, R. E. Murillo Muñoz, ed., CRC Press, Boca Raton, FL, 1021–1028.
Breckpot, M., Agudelo, O. M., and De Moor, B. (2012b). “Model predictive control of a river system with two reaches.” Proc., 51st IEEE Conf. on Decision and Control, IEEE, New York.
Breckpot, M., Barjas Blanco, T., and De Moor, B. (2010). “Flood control of rivers with nonlinear model predictive control and moving horizon estimation.” Proc., 49th IEEE Conf. on Decision and Control, IEEE, New York, 6107–6112.
Burt, C. M., Mills, R. S., Khalsa, R. D., and Ruiz, V. (1998). “Improved proportional-integral (PI) logic for canal automation.” J. Irrig. Drain. Eng., 124(1), 53–57.
Chaudry, M. H. (2008). Open-channel flow, 2nd Ed., Springer, New York.
Chow, V. T. (1959). Open-channel hydraulics, McGraw-Hill, New York.
Clemmens, A. J., Bautista, E., Wahlin, B. T., and Strand, R. J. (2005). “Simulation of automatic canal control systems.” J. Irrig. Drain. Eng., 131(4), 324–335.
Cunge, J. A., Holly, F. M., and Verwey, A. (1980). Practical aspects of computational river hydraulics, Pitman, London.
Franklin, G. F., Powell, D. J., and Workman, M. L. (1997). Digital control of dynamic systems, 3rd Ed., Addison-Wesley, Boston, MA.
Henderson, F. M. (1966). Open channel flow, Macmillan, New York.
Hovd, M., and Braatz, R. D. (2001). “Handling state and output constraints in MPC using time-dependent weights.” Proc., American Control Conf. (ACC), IEEE, New York.
Kalman, R. E. (1960). “A new approach to linear filtering and prediction problems.” J. Basic Eng., 82, 35–45.
Kwakernaak, H., and Sivan, R. (1972). Linear optimal control systems, Wiley-Interscience, New York.
Liggett, J. A., and Cunge, J. A. (1975). Numerical methods of solution of the unsteady flow equations, unsteady flow in open channels, Chapter 4, Water Resources Publications, Fort Collins, CO.
Lin, C. H., Yen, J. F., and Tsai, C. T. (2002). “Influence of sluice gate contraction coefficient on distinguishing condition.” J. Irrig. Drain. Eng., 128(4), 249–252.
Litrico, X., and Fromion, V. (2009). Modeling and control of hydrosystems, Springer-Verlag, New York.
Litrico, X., Fromion, V., and Baume, J. P. (2006). “Tuning of robust distant downstream PI controllers for an irrigation canal pool—II. Implementation issues.” J. Irrig. Drain. Eng., 132(4), 369–379.
Malaterre, P. O., and Baume, J. P. (1999). “Optimum choice of control action variables and linked algorithms. Comparison of different alternatives.” Proc., Workshop on Modernization of Irrigation Water Delivery Systems, USCID, Phoenix, 387–406.
Malaterre, P. O., Rogers, D. C., and Schuurmans, J. (1998). “Classification of canal control algorithms.” J. Irrig. Drain. Eng., 124(1), 3–10.
MATLAB 3 (2011a). [Computer software]. MathWorks, Natick, MA.
Mayne, Q., Rawlings, J. B., Rao, C. V., and Scokaert, P. O. M. (2000). “Constrained model predictive control: Stability and optimality.” Automatica, 36(6), 789–814.
Negenborn, R. R., van Overloop, P.-J., Keviczky, T., and De Schutter, B. (2009). “Distributed model predictive control of irrigation canals.” Networks Heterog. Media, 4(2), 359–380.
Nocedal, J., and Wright, S. J. (2000). Numerical optimization, Springer, New York.
Puig, V., et al. (2009). “Optimal predictive control of water transport systems: Arrêt-Darré/Arros case study.” Water Sci. Technol., 60(8), 2125–2133.
Qin, S., and Badgwell, T. (2003). “A survey of industrial model predictive control technology.” Control Eng. Pract., 11(7), 733–764.
Romera, J., Ocampo-Martnez, C., Puig, V., Quevedo, J., Garca, P., and Prez, G. (2011). “Flooding management using hybrid model predictive control at the Ebro River in Spain.” Proc., 8th IWA Symp. on System Analysis and Integrated Assessment, IWA, San Sebastian, Spain, 1–8.
Rossiter, J. (2003). Model-based predictive control, CRC, Boca Raton, FL.
Schuurmans, J. (1997). “Control of water levels in open channels.” Ph.D. thesis, Delft Univ. of Technology, Delft, Netherlands.
Scokaert, P. O. M., and Rawlings, J. B. (1999). “Feasibility issues in linear model predictive control.” AIChE J., 45(8), 1649–1659.
Sepúlveda, C., Gómez, M., and Rodellar, J. (2009). “Benchmark of discharge calibration methods for submerged sluice gates.” J. Irrig. Drain. Eng., 135(5), 676–682.
Strelkoff, T. S., and Falvey, H. T. (1993). “Numerical methods used to model unsteady canal flow.” J. Irrig. Drain. Eng., 119(4), 637–655.
Sturm, T. W. (2001). Open channel hydraulics. McGraw-Hill, New York.
Thai, T. (2005). “Numerical methods for parameter estimation and optimal control for the Red River Network.” Ph.D. thesis, Universität Heidelberg, Heidelberg, Germany.
Van Overloop, P. J. (2006). “Model predictive control of open water systems.” Ph.D. thesis, Technische Universiteit Delft, Delft, Netherlands.
Van Overloop, P. J., Clemmens, A. J., Strand, R. J., Wagemaker, R. M. J., and Bautista, E. (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.
Van Overloop, P.-J., Schuurmans, J., Brouwer, R., and Burt, C. M. (2005). “Multiple-model optimization of proportional integral controllers on canals.” J. Irrig. Drain. Eng., 131(2), 190–196.
Van Overloop, P.-J., Weijs, S., and Dijkstra, S. (2008). “Multiple model predictive control on a drainage canal system.” Control Eng. Pract., 16(5), 531–540.
Wahlin, B., and Clemmens, A. J. (2006). “Automatic downstream water-level feedback control of branching canal networks: Theory.” J. Irrig. Drain. Eng., 132(3), 208–219.
Xu, M., van Overloop, P. J., and van de Giesen, N. C. (2011). “On the study of control effectiveness and computational efficiency of reduced Saint-Venant model in model predictive control of open channel flow.” Adv. Water Resour., 34(2), 282–290.

Information & Authors

Information

Published In

Go to Journal of Irrigation and Drainage Engineering
Journal of Irrigation and Drainage Engineering
Volume 139Issue 7July 2013
Pages: 532 - 541

History

Received: Jun 20, 2012
Accepted: Jan 14, 2013
Published online: Jan 16, 2013
Published in print: Jul 1, 2013

Permissions

Request permissions for this article.

Authors

Affiliations

Maarten Breckpot [email protected]
Ph.D. Fellow, Research Foundation—Flanders (FWO), Dept. of Electrical Engineering-ESAT (SCD-SISTA), KU Leuven, Kasteelpark Arenberg 10, B-3001 Leuven, Belgium (corresponding author). E-mail: [email protected]
Oscar Mauricio Agudelo [email protected]
Postdoctoral Researcher, Dept. of Electrical Engineering-ESAT (SCD-SISTA), KU Leuven, Kasteelpark Arenberg 10, B-3001 Leuven, Belgium. E-mail: [email protected]
Bart De Moor [email protected]
Full Professor, Dept. of Electrical Engineering-ESAT (SCD-SISTA)/iMinds Future Health Dept. KU Leuven, Kasteelpark Arenberg 10, B-3001 Leuven, Belgium. E-mail: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share