Data Driven System Identification of Water Distribution Systems via Kernel-Based Interpolation
Publication: World Environmental and Water Resources Congress 2024
ABSTRACT
Water distribution systems (WDSs) are critical infrastructure demanding effective control for optimal pressure and flow. Existing control algorithms rely on accurate system models, a challenging task for large-scale WDSs due to complex, nonlinear hydraulics. This work proposes a data-driven system identification using kernel-based interpolation, assuming general WDS dynamics without prior knowledge of the true basis functions. Leveraging WDSs’ automation, such as water level and flow sensors, this method constructs a regularized interpolated kernel-based model based on input-output pairs. Compared to state-of-the-art system identification, the predicted model offers deterministic bounds on the approximation error to enhance the accuracy. Given that WDSs are changing over time, this approach is useful to ensure that the controller is adept with the changing dynamics of WDS. The proposed method is validated on four interconnected water tanks, representing simplified WDSs yet equipped with WDSs’ nonlinearities. The results demonstrate high accuracy with errors varying from 0.02% to 3%.
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Information & Authors
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Published In
World Environmental and Water Resources Congress 2024
Pages: 283 - 296
History
Published online: May 16, 2024
ASCE Technical Topics:
- Continuum mechanics
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Equipment and machinery
- Errors (statistics)
- Hydraulic models
- Infrastructure
- Lifeline systems
- Mathematics
- Model accuracy
- Models (by type)
- Pressure (type)
- Solid mechanics
- Statistics
- Tanks (by type)
- Water and water resources
- Water management
- Water pressure
- Water supply
- Water supply systems
- Water tanks
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