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Abstract
Real-time control of urban drainage networks requires knowledge about stored volumes and flows in order to predict overflows and optimize system operation. However, using flow sensors inside the pipelines means prohibitively high installation and maintenance costs. In this article, we formulate two nonlinear, constrained estimation problems for identifying the open-channel flow in urban drainage networks. To this end, we distribute cost-efficient level sensors along the pipelines and formulate the estimation problems based on the spatially-discretized kinematic and diffusion wave approximations of the full Saint-Venant partial differential equations. To evaluate the capabilities of the two models, the two approaches are compared and evaluated on modeling a typical phenomenon occurring in drainage systems: the backwater effect. An extensive real-world experiment demonstrates the effectiveness of the two approaches in obtaining the model parameters on a scaled water laboratory setup, in the presence of measurement noise.
Original language | English |
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Title of host publication | 2021 IEEE Conference on Control Technology and Applications (CCTA) |
Number of pages | 6 |
Place of Publication | San Diego |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
Publication date | Aug 2021 |
Pages | 1202-1207 |
Article number | 9658864 |
ISBN (Print) | 978-1-6654-3644-1 |
ISBN (Electronic) | 978-1-6654-3643-4 |
DOIs | |
Publication status | Published - Aug 2021 |
Event | 2021 IEEE Conference on Control Technology and Applications (CCTA) - San Diego, United States Duration: 9 Aug 2021 → 11 Aug 2021 |
Conference
Conference | 2021 IEEE Conference on Control Technology and Applications (CCTA) |
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Country/Territory | United States |
City | San Diego |
Period | 09/08/2021 → 11/08/2021 |
Series | IEEE Conference on Control Technology and Applications (CCTA) - Proceedings |
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ISSN | 2768-0762 |
Keywords
- System Identification
- backwater effect
- Urban Drainage
- Smart Water Infrastructures Laboratory
- SWIL
- nonlinear modeling
- Partial Differential Equation
- Energy system
- green lab
- water infrastructures
- Sewer
- Waste Water
- Disturbance
- Saint-Venant
- Kinematic Wave Model
- Diffusion Wave model
- Optimization
Fingerprint
Dive into the research topics of 'Nonlinear Grey-box Identification of Gravity-driven Sewer Networks with the Backwater Effect: An Experimental Study'. Together they form a unique fingerprint.Projects
- 1 Finished
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Stochastic Model Predictive Control of Combined Sewer Overflows in Sanitation Networks
Hodzic, A. (Project Participant), Knudsen, C. H. (Project Participant), Balla, K. M. (Supervisor) & Kallesøe, C. S. (Supervisor)
01/09/2020 → 03/06/2021
Project: Research
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Equipment
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Smart Water Infrastructures Laboratory (SWIL)
Ledesma, J. V. (Operator), Wisniewski, R. (Manager), Kallesøe, C. (Operator), Rathore, S. S. (Manager), Misra, R. (Manager), Sawant, V. S. (Manager) & Mazumdar, A. (Manager)
Department of Electronic SystemsFacility: Laboratory