Nonlinear Grey-box Identification of Gravity-driven Sewer Networks with the Backwater Effect: An Experimental Study

Krisztian Mark Balla*, Casper Houtved Knudsen, Adis Hodzic, Jan Dimon Bendtsen, Carsten Kallesøe

*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

2 Citationer (Scopus)
56 Downloads (Pure)

Abstrakt

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.
OriginalsprogEngelsk
Titel2021 IEEE Conference on Control Technology and Applications (CCTA)
Antal sider6
UdgivelsesstedSan Diego
ForlagIEEE
Publikationsdatoaug. 2021
Sider1202-1207
Artikelnummer9658864
ISBN (Trykt)978-1-6654-3644-1
ISBN (Elektronisk)978-1-6654-3643-4
DOI
StatusUdgivet - aug. 2021
Begivenhed2021 IEEE Conference on Control Technology and Applications (CCTA) - San Diego, USA
Varighed: 9 aug. 202111 aug. 2021

Konference

Konference2021 IEEE Conference on Control Technology and Applications (CCTA)
Land/OmrådeUSA
BySan Diego
Periode09/08/202111/08/2021
NavnIEEE Conference on Control Technology and Applications (CCTA) - Proceedings
ISSN2768-0762

Fingeraftryk

Dyk ned i forskningsemnerne om 'Nonlinear Grey-box Identification of Gravity-driven Sewer Networks with the Backwater Effect: An Experimental Study'. Sammen danner de et unikt fingeraftryk.

Citationsformater