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CONTROLO 2016 pp 275-284 | Cite as

Data Based Modeling of a Large Scale Water Delivery System

  • Marta FernandesEmail author
  • Paulo Oliveira
  • Susana Vieira
  • Luís Mendonça
  • João Lemos Nabais
  • Miguel Ayala Botto
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 402)

Abstract

Water is a vital resource and the growing populations and economies around the globe are pushing its demand worldwide. Therefore, the water conveyance operation should be well managed and improved. This paper proposes the development of reliable models able to predict water levels of a real 24.4 km water delivery channel in real time. This is a difficult task because this is a time-delayed dynamical system distributed over a long distance with nonlinear characteristics and external perturbations. Artificial neural networks are used, which are a well-known modeling technique that has been applied to complex and nonlinear systems. Real data is used for the design and validation of the models. The model obtained has the ability to predict water levels along the channel with minimum error, which can result in significant reduction of wasted water when implementing an automatic controller.

Keywords

Data based modeling Water delivery systems Artificial neural networks Nonlinear autoregressive exogenous model 

Notes

Acknowledgments

This work is supported by the Fundação para a Ciência e a Tecnologia (FCT), through IDMEC, under LAETA Pest-OE/EME/LA0022, and supported by the project PTDC/EMS-CRO/2042/2012. Susana Vieira acknowledges the support by the Program Investigador FCT (IF/00833/2014) from FCT, cofunded by the European Social Fund (ESF) through the Operational Program Human Potential (POPH).

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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Marta Fernandes
    • 1
    Email author
  • Paulo Oliveira
    • 1
  • Susana Vieira
    • 1
  • Luís Mendonça
    • 1
    • 2
  • João Lemos Nabais
    • 1
    • 3
  • Miguel Ayala Botto
    • 1
  1. 1.IDMEC, LAETA, Instituto Superior TécnicoUniversidade de LisboaLisbonPortugal
  2. 2.Department of Marine EngineeringEscola Superior Náutica Infante D. HenriqueOeirasPortugal
  3. 3.School of Business AdministrationPolytechnical Institute of SetúbalSetúbalPortugal

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