| 引用本文: | 卿光志,黄 草,王 睿,等.水闸群耦合式MPC控制模式与算法研究[J].灌溉排水学报,2025,44(12):45-56. |
| QING Guangzhi,HUANG Cao,WANG Rui,et al.水闸群耦合式MPC控制模式与算法研究[J].灌溉排水学报,2025,44(12):45-56. |
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| 摘要: |
| 【目的】大型长距离调水工程的输水时滞和闸群协同问题影响了闸群控制的效率，本研究旨在进一步提高大型调水工程闸群的调控效率，优化闸群控制模式。【方法】设计了集总式（CMPC）、分布式（DMPC）、耦合式（D-CMPC）3种基于MPC算法的闸群控制与算法，对比分析了目标水位变化及分水扰动等9种情景下，不同控制模式对南水北调中线工程36#~41#闸群的闸前水位和过闸流量的控制效果。【结果】在目标水位控制方面，相较于CMPC模式和DMPC模式，D-CMPC模式下调控效率提升幅度达19%~71%，累计波动降幅为14%~79%。在应对分水扰动时，D-CMPC模式下的水位稳定性最佳，水位变化幅度最小。【结论】耦合式MPC闸群控制可为大型调水工程的自动化与智能化提供了技术支持。 |
| 关键词: 耦合式MPC；水闸群；控制模式；控制算法；南水北调 |
| DOI：10.13522/j.cnki.ggps.2025145 |
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| Using model predictive control algorithm to improve gate group control in large-and long-distance water transfer project |
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QING Guangzhi, HUANG Cao, WANG Rui, QIN Hui, LEI Xiaohui
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1. Changsha University of Science and Technology, Changsha 410114, China; 2. China Building Materials Inspection & Certification Group Hunan Co., Ltd, Changsha 410036, China; 3. Hunan Provincial Key Laboratory of Water Environment Management and Ecological Rehabilitation of Dongting Lake, Changsha 410114, China; 4. Huazhong University of Science and Technology,
Wuhan 430074, China; 5. Hebei University of Engineering, Handan 056038, China
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| Abstract: |
| 【Objective】Large-scale, long-distance water transfer projects are critical for balancing spatial water resource distribution, but their gate group control faces lags in water transfer time, poor synergy and ‘dimensional disasters’ in centralized control, which hinder control efficiency and precision. Distributed control can alleviate these limitations but could lead to subsystem coupling and decoupling losses. We proposed a method in this paper to optimize the gate group control using the model predictive control (MPC), to improve water resource control accuracy and use efficiency in automation and intelligent construction of engineering projects.【Method】Three MPC-based gate group control model were designed: centralized model predictive control (CMPC), distributed model predictive control (DMPC), and coupled distributed-centralized model predictive control (D-CMPC). Their performance was tested and compared against the 36#–41# Gate Section in the South-to-North Water Diversion Middle Line Project under nine different combinations of targeted water level changes and water diversion disturbances. The analysis focused on the effects of the control on gate-section water levels and over-gate flow. 【Result】For targeted water level control, D-CMPC outperformed CMPC and DMPC, and its regulation efficiency improved by 19%-71%, and cumulative water level fluctuations decreased by 14% to 79%. In respondence to water diversion disturbances, D-CMPC was also the best in keeping water level stability. 【Conclusion】The coupled MPC-based gate group control strategy (D-CMPC) effectively resolves the key challenges in large-scale water transfer project control, providing a robust technical support for helping design automation and intelligent upgrading of hydraulic engineering projects. |
| Key words: Coupled MPC; sluice group; control mode; control algorithm; South-to-North Water Transfer |
