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  4. Vol 9, Issue 4, 2025

Robust Multi-Lake Water-Level Regulation via Network-Flow–Informed PID Control with PSO Tuning and Global Sensitivity Analysis

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DOI: 10.23977/acss.2025.090401 | Downloads: 6 | Views: 98

Author(s)

Jiahao Fan 1

Affiliation(s)

1 Hainan International College, Communication University of China, Lingshui Lizu Autonomous County, Hainan, China

Corresponding Author

Jiahao Fan

ABSTRACT

Effective water-level regulation across interconnected lakes is essential for flood prevention, ecological balance, and sustainable hydropower operation. This study proposes a hybrid control and optimization framework integrating physical network-flow modelling, constrained optimization, and intelligent control parameter tuning. First, the Great Lakes system is represented as a directed network that captures inflows, outflows, and hydrological couplings. The optimal target levels of each lake are determined using Sequential Least-Squares Quadratic Programming (SLSQP) under multi-objective constraints of ecological stability and energy efficiency. A proportional–integral–derivative (PID) controller is then established to regulate outflows, and its parameters are automatically tuned by Particle Swarm Optimization (PSO) to minimize a composite performance index consisting of steady-state error, overshoot, and rise time. Furthermore, a global sensitivity analysis based on the Sobol method is conducted to quantify the influence of hydrological and climatic factors—including precipitation, evaporation, snowmelt, and temperature—on water-level dynamics. Simulation results show that the optimized controller effectively tracks target water levels with reduced overshoot and shorter adjustment time compared with conventional PID control. The sensitivity results reveal that precipitation and snowmelt dominate overall variance, highlighting seasonal vulnerability. The proposed framework demonstrates strong robustness and adaptability, providing a reliable approach for large-scale lake system regulation and sustainable water resource management.

KEYWORDS

Water-Level Regulation; Network-Flow Model; PID Control; Particle Swarm Optimization (PSO); Sobol Sensitivity Analysis; Multi-Objective Optimization; Great Lakes System

CITE THIS PAPER

Jiahao Fan, Robust Multi-Lake Water-Level Regulation via Network-Flow–Informed PID Control with PSO Tuning and Global Sensitivity Analysis. Advances in Computer, Signals and Systems (2025) Vol. 9: 1-9. DOI: http://dx.doi.org/10.23977/acss.2025.090401.

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