A HIGH-PERFORMANCE COMPUTING (HPC) BASED INTEGRATED MULTITHREADED MODEL PREDICTIVE CONTROL (MPC) FOR WATER SUPPLY NETWORKS

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Architecture, Civil Engineering, Environment

Silesian University of Technology

Subject: Architecture , Civil Engineering , Engineering, Environmental

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VOLUME 10 , ISSUE 4 (December 2017) > List of articles

A HIGH-PERFORMANCE COMPUTING (HPC) BASED INTEGRATED MULTITHREADED MODEL PREDICTIVE CONTROL (MPC) FOR WATER SUPPLY NETWORKS

Krzysztof GASKA / Agnieszka GENEROWICZ / Izabela ZIMOCH / Józef CIUŁA / Zsuzsanna IWANICKA

Keywords : SMART City, Water distribution systems, Sewerage systems, Predictive models (MPC), Artificial intelligence, GIS, Parallel computing architecture (HPC)

Citation Information : Architecture, Civil Engineering, Environment. VOLUME 10 , ISSUE 4 , ISSN (Online) , DOI: 10.21307/acee-2017-058, December 2017 © 2017.

License : (BY-NC-ND 4.0)

Published Online: 28-August-2018

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ABSTRACT

The article presents the concept of an intelligent system of multithreaded, hierarchical predictive control of water supply and sewage networks using a parallel computational architecture. The predominant element of the proposed control system over other hitherto functioning systems is the element of predicting future events (MPC model). This feature, combined with the self-learning intelligent control system, not only allows you to react to changes in sensor state, but also anticipate these changes and adjust the system in advance to prepare for predicted situation, which is particularly important in systems with high inertia as extensive water supply and sewage networks. The technologically advanced solutions proposed by the authors, ie the HPC (High Performance Computing) ICT system, including the requesting module allows (by analyzing the space of states and events in real time) to predict future behaviors of individual elements of the system and effectively react to unknown cases, supporting the making of strategic decisions.

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[1] Akouz, K., Benhammou, A., Malaterre, P. O., Dahbou, B., Roux, G. (1998). Predictive control applied to ASCE canal 2. in Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics, San Diego, California, 3920-3924.

[2] Barjas Blanco, T., Willems, P., De Moor, B., Berlamont, J. (2008). Flood prevention of the Demerusing model predictive control. in Proceedings of the 17th IFAC World Congress, Seoul, Korea, 3629-3634.

[3] Begovich, O., Ruiz, V. M., Besançon, G., Aldana, C. I., Georges D. (2007). Predictive control with constraints of a multi-pool irrigation canal prototype. Latin American Applied Research, 37(3), 177-185.

[4] Eker, I., Kara, T., (2003). Operation and control of a water supply system. ISA Transactions, 42(3), 461-473.

[5] El Fawal, H., Georges, D., Bornard, G. (1998). Optimal control of complex irrigation systems via decomposition-coordination and the use of augmented Lagrangian. in Proceedings of the 1998 International Conference on Systems, Man, and Cybernetics, San Diego, California, 3874-3879.

[6] Gaska, K., Generowicz, A. (2017). Advanced computational methods in component-oriented modeling of municipal solid waste incineration processes. Architecture Civil Engineering Environment, 10(1), 117-130.

[7] Gaska, K., Wandrasz, A.J. (2008). Mathematical modelling of biomass fuels formation process. Waste Management, 28(6), 973-985.

[8] Georges, D. (1994). Decentralized adaptive control for a water distribution system. in Proceedings of the 3rd IEEE Conference on Control Applications, Glasgow, UK, 1411-1416.

[9] Kowalski, Z., Generowicz, A., Makara, A. (2012). Evaluation of municipal waste disposal technologies. Przemysł Chemiczny, 91(5), 811-815.

[10] Maciejowski, J. (2002). M. Predictive Control with Constraints. Harlow, UK: Prentice-Hall,

[11] Mays, L. W. (1999). Hydraulic Design Handbook. New York, New York: McGraw-Hill Professional Publishing,

[12] Mikosz, J. (2013). Wastewater management in small communities in Poland. Desalination & Water Treatment 51(10-12), 2461-2466.

[13] Mucha, Z., Kurbiel-Swatek K. (2016). Analysis of membrane reactors applications for municipal wastewater treatment plants. Przemysł Chemiczny, 95(2), 236-240.

[14] Negenborn, R. R., De Schutter, B., Hellendoorn, J. (2008). Multi-agent model predictive control for transportation networks: Serial versus parallel schemes. Engineering Applications of Artificial Intelligence, 21(3), 353-366.

[15] Negenborn, R. R., van Overloop, P. J., Keviczky, T., De Schutter B. (2009). Distributed model predictive control for irrigation canals. Networks and Heterogeneous Media, 4(2), 359-380.

[16] Sawadogo, S., Faye, R. M., Malaterre, P. O., Mora-Camino, F. (1998). Decentralized predictive controller for delivery canals. in Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics, San Diego, California, 3380-3884.

[17] Vairavamoorthy, K., Gorantiwar, S. D., Pathirana, A. (2008). Managing urban water supplies in developing countries - Climate change and water scarcity scenarios. Physics and Chemistry of the Earth, 33(5), 330-339.

[18] Wahlin, B. T., Clemmens, A. J. (2006). Automatic downstream water-level feedback control of branching canal networks: Simulation results. Journal of Irrigation and Drainage Engineering, 132(3), 208-219.

[19] Walski, T. M., Chase, D. V., Savic, D. A., Grayman, W., Beckwith, S., Koelle, E. (2003). Advanced Water Distribution Modeling and Management. Waterbury, Connecticut: Haestead Press.

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