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Model Predictive Control-Based Hydrodynamic Regulation Framework for the Lower Ganjiang River
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DOI：10.3390/hydrology13080203.png)
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Abstract
En 中文
The Lower Ganjiang River is a multi-branch delta with highly uneven spatial and temporal flow distribution, and conventional static diversion or threshold-based operation fails to stabilise the water level or optimise flow allocation under varying inflows. This study develops a hydrodynamic regulation framework that couples an improved integral time-delay model and model predictive control (MPC). A nonlinear state-space equation is constructed using a quadratic storage–water level relationship and rolling optimisation is solved with CasADi-IPOPT to minimise water-level tracking error, discharge deviation and control effort. The framework is validated offline against MIKE21 simulations for three historical flow scenarios (September 2016, February 2017 and March 2018). Under these scenarios, the Waizhou water level is maintained at 15.5 ± 0.2 m, daily water level variation is limited to ≤0.5 m/d, and the diversion ratio deviation is ≤5%. Compared with the natural state, water level fluctuation is reduced by 21.3% (September 2016 storage scenario). The proposed MPC framework effectively alleviates the spatiotemporal hydrodynamic imbalance of the Lower Ganjiang River, showing satisfactory model accuracy, constraint compliance, and engineering applicability, and offers a promising approach for advanced regulation of complex multi-branch river networks.
Keywords:
model predictive control
Lower Ganjiang River
hydrodynamic reconstruction
multi-objective optimization
Journal
H
IF:
3.2
Papers:
299
Citations:
0