摘要
【目的】提高多级闸控河渠水位变幅较大时的河渠水位控制精度,减小河渠水位振荡,提升控制算法的收敛效率。【方法】利用河渠实时水位动态修正ID模型参数并调整闸坝启闭频率,提出自适应预测控制(APC)算法,对比分析6种工况下不同控制算法的精度与效率。【结果】与基于ID模型的线性二次型控制(LQR)算法与模型预测控制(MPC)算法相比,APC算法可分别缩短19%~32%和8%~40%的调控时长,可减少47%~97%和14%~93%的河渠水位累计波动,可减小24%~77%和5%~59%的河渠水位平均绝对偏差。【结论】APC算法提高了多级闸控河渠水位的控制精度和算法的收敛性,可在不同的河渠水位变幅下保持良好的控制性能,能够为多级闸控河渠的智慧水利建设提供技术支持。
【Objective】The aim of this study is to improve the accuracy of water level control,minimize water level oscillations,and improve the convergence efficiency of control algorithms for multi-stage gate-controlled canals operating under significant water level variations.【Method】We propose an adaptive predictive control algorithm(APC)which dynamically adjusts the parameters of the identification(ID)model based on real-time canal water level data and modifies the activation frequency of sluices.The performance of the APC algorithm is comprehensively evaluated and compared with other control algorithms under six distinct operational conditions.【Result】In comparison to the linear quadratic controller(LQR)and the model predictive controller(MPC)based on the ID model,the APC algorithm shows significant improvements in accuracy and reliability,reducing the regulation duration by 19%to 32%and 8%to 40%respectively,damping the cumulative fluctuation of the canal water level by 47%to 97%and 14%to 93%respectively,lowering the mean absolute deviation of canal water level by 24%to 77%and 5%to 59%,respectively.【Conclusion】The APC method can substantially improve the precision of water level control and the convergence for multi-stage gate-controlled canals.It is robust for various canal water level amplitudes,thereby providing a crucial technical support for advancing intelligent management of water conservancy infrastructures.
作者
杨忆昕
黄草
刘晋龙
李威岐
曹劲松
YANG Yixin;HUANG Cao;LIU Jinlong;LI Weiqi;CAO Jinsong(School of Hydraulic and Environmental Engineering,Changsha University of Science&Technology,Changsha 410114,China;Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and Restoration of Hunan Province,Changsha University of Science&Technology,Changsha 410114,China;Beijing General Municipal Engineering Design&Research Institute Co.,Ltd,Beijing 100082,China)
出处
《灌溉排水学报》
CAS
CSCD
2024年第4期66-73,共8页
Journal of Irrigation and Drainage
基金
国家自然科学基金面上项目(52179004)
湖南省水利科技项目(XSKJ2022068-04)
长沙理工大学研究生科研创新项目(CXCLY2022069)。
关键词
沙河
实时控制
积分时滞模型
模型预测控制
自适应方法
Sha-River
real-time control
integrator-delay model
model predictive control
adaptive method
作者简介
杨忆昕(1999-),男,福建福清人。硕士研究生,主要从事水资源管理研究。E-mail:yangyixin7009@163.com;通信作者:黄草(1985-),男,湖南衡阳人。副教授,主要从事水资源配置和水资源管理研究。E-mail:huangcao@outlook.com。
