PID Controllers as Data Assimilation Tool for 1D Hydrodynamic Models of Different Complexity
Apstrakt
Flood risks management is based on data obtained by different forecasts. Forecasts are often based on hydrological-hydrodynamic models. These models are calibrated using selected time-series from the past. However, even calibrated models in later exploitation phases can produce solutions of unsatisfying accuracy. Some of the reasons are uncertainty in the initial and boundary conditions, uncertainty of the input data and uncertainty in riverbed geometry. The aim of the assimilation is to improve the results obtained from the previously calibrated model by coupling it with observed data. To assimilate, the model is run for a short previous period and the state of the model is adjusted to observed data. The corrected model state is then used as an initial state to run the model with for short-term forecast of input data. Assimilation method based on the PID controller for 1D river hydrodynamic models is analyzed in this paper. This method adjusts the state in the hydrodynamic models acco...rding to the measurements indirectly by adding or subtracting the discharge in the junction/sections with measured water level. The influence of the hydrodynamic model complexity is analyzed, comparing three models: non-inertia model, diffusion wave and dynamic wave model. Results show that PID control can be adequately used even coupled with simplified hydraulic models for short-term assimilation and forecast, without significant loss of accuracy. PID control-based data assimilation also yields significant reduction in the computational runtime.
Ključne reči:
Control loop feedback mechanism / Data assimilation / short-term forecasting / Non-inertial model / Diffusion wave / Dynamic waveIzvor:
Advances in Hydroinformatics - SimHydro 2019, 2019Izdavač:
- Springer
Kolekcije
Institucija/grupa
GraFarTY - CONF AU - Milašinović, Miloš AU - Zindović, Budo AU - Rosić, Nikola AU - Prodanović, Dušan PY - 2019 UR - https://grafar.grf.bg.ac.rs/handle/123456789/2093 AB - Flood risks management is based on data obtained by different forecasts. Forecasts are often based on hydrological-hydrodynamic models. These models are calibrated using selected time-series from the past. However, even calibrated models in later exploitation phases can produce solutions of unsatisfying accuracy. Some of the reasons are uncertainty in the initial and boundary conditions, uncertainty of the input data and uncertainty in riverbed geometry. The aim of the assimilation is to improve the results obtained from the previously calibrated model by coupling it with observed data. To assimilate, the model is run for a short previous period and the state of the model is adjusted to observed data. The corrected model state is then used as an initial state to run the model with for short-term forecast of input data. Assimilation method based on the PID controller for 1D river hydrodynamic models is analyzed in this paper. This method adjusts the state in the hydrodynamic models according to the measurements indirectly by adding or subtracting the discharge in the junction/sections with measured water level. The influence of the hydrodynamic model complexity is analyzed, comparing three models: non-inertia model, diffusion wave and dynamic wave model. Results show that PID control can be adequately used even coupled with simplified hydraulic models for short-term assimilation and forecast, without significant loss of accuracy. PID control-based data assimilation also yields significant reduction in the computational runtime. PB - Springer C3 - Advances in Hydroinformatics - SimHydro 2019 T1 - PID Controllers as Data Assimilation Tool for 1D Hydrodynamic Models of Different Complexity DO - 10.1007/978-981-15-5436-0_76 ER -
@conference{ author = "Milašinović, Miloš and Zindović, Budo and Rosić, Nikola and Prodanović, Dušan", year = "2019", abstract = "Flood risks management is based on data obtained by different forecasts. Forecasts are often based on hydrological-hydrodynamic models. These models are calibrated using selected time-series from the past. However, even calibrated models in later exploitation phases can produce solutions of unsatisfying accuracy. Some of the reasons are uncertainty in the initial and boundary conditions, uncertainty of the input data and uncertainty in riverbed geometry. The aim of the assimilation is to improve the results obtained from the previously calibrated model by coupling it with observed data. To assimilate, the model is run for a short previous period and the state of the model is adjusted to observed data. The corrected model state is then used as an initial state to run the model with for short-term forecast of input data. Assimilation method based on the PID controller for 1D river hydrodynamic models is analyzed in this paper. This method adjusts the state in the hydrodynamic models according to the measurements indirectly by adding or subtracting the discharge in the junction/sections with measured water level. The influence of the hydrodynamic model complexity is analyzed, comparing three models: non-inertia model, diffusion wave and dynamic wave model. Results show that PID control can be adequately used even coupled with simplified hydraulic models for short-term assimilation and forecast, without significant loss of accuracy. PID control-based data assimilation also yields significant reduction in the computational runtime.", publisher = "Springer", journal = "Advances in Hydroinformatics - SimHydro 2019", title = "PID Controllers as Data Assimilation Tool for 1D Hydrodynamic Models of Different Complexity", doi = "10.1007/978-981-15-5436-0_76" }
Milašinović, M., Zindović, B., Rosić, N.,& Prodanović, D.. (2019). PID Controllers as Data Assimilation Tool for 1D Hydrodynamic Models of Different Complexity. in Advances in Hydroinformatics - SimHydro 2019 Springer.. https://doi.org/10.1007/978-981-15-5436-0_76
Milašinović M, Zindović B, Rosić N, Prodanović D. PID Controllers as Data Assimilation Tool for 1D Hydrodynamic Models of Different Complexity. in Advances in Hydroinformatics - SimHydro 2019. 2019;. doi:10.1007/978-981-15-5436-0_76 .
Milašinović, Miloš, Zindović, Budo, Rosić, Nikola, Prodanović, Dušan, "PID Controllers as Data Assimilation Tool for 1D Hydrodynamic Models of Different Complexity" in Advances in Hydroinformatics - SimHydro 2019 (2019), https://doi.org/10.1007/978-981-15-5436-0_76 . .