广西师范大学学报（自然科学版） ›› 2018, Vol. 36 ›› Issue (1): 53-60.doi: 10.16088/j.issn.1001-6600.2018.01.007

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大坝—河流渠道灌溉系统的迭代学习控制

戴喜生1,2*,李光1,3,周星宇1   

  1. 1.广西科技大学电气与信息工程学院,广西柳州545006;
    2.桂林电子科技大学智能综合自动化高校重点实验室,广西桂林541004;
    3.广东工商职业学院智能制造学院,广东肇庆526020
  • 收稿日期:2017-05-30 出版日期:2018-01-20 发布日期:2018-07-17
  • 通讯作者: 戴喜生(1976—),男,湖北黄冈人,广西科技大学教授,博士。E-mail:mathdxs@163.com
  • 基金资助:
    国家自然科学基金(61364006);广西自然科学基金(2017GXNSFAA198179);广西高等学校优秀中青年骨干教师培养工程(桂教人[2014]39号);智能综合自动化高校重点实验室基金(智字201502)

Iterative Learning Control of Dam-River Channel Irrigation Systems

DAI Xisheng1,2*,LI Guang 1,3 ,ZHOU Xingyu1   

  1. 1. School of Electrical and Information Engineering,Guangxi University of Science and Technology,Liuzhou Guangxi 545006,China;
    2. Colleges and Universities Key Laboratory of Intelligent Integrated Automation, Guilin University of Electronic Technology,Guilin Guangxi 541004,China;
    3. School of Intelligent Manufacturing, Guangdong College of Business and Technology,Zhaoqing Guangdong 526020,China
  • Received:2017-05-30 Online:2018-01-20 Published:2018-07-17

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摘要： 本文考虑大坝—河流渠道灌溉系统的迭代学习控制问题。首先,对线性化的Hayami偏微分方程在空间上离散化,通过叠加向量方法建立闸门与流量关系的状态空间数学模型;其次,结合灌溉过程的重复性特点,设计D型迭代学习控制算法,建立了该算法的收敛性条件。结果表明通过闸门开度的迭代学习控制,可实现对取水口期望流量的完全跟踪。最后,通过数值仿真进一步说明提出的迭代学习控制方法的有效性。

关键词: 迭代学习控制, 灌溉系统, Hayami方程, 离散化

Abstract: The iterative learning control problem of dam-river channel irrigation system is investigated in this paper. Firstly,the Hayami equation of the linearized equation is discretized in space,and the state space mathematical model of the relationship between gate and flow is established by superposition vector method. Secondly,based on the repetitive characteristics of irrigation process,a D-type iterative learning control algorithm is designed,and the convergence condition of the algorithm is also proposed. The results show that the iterative learning control of opening degree of the gate can make the actual output of the system completely track the expected flow rate in the channel. Finally,the validity of the proposed iterative learning control is illustrated by numerical simulation.

Key words: iterative learning control, irrigation system, Hayami equation, discretization

中图分类号: 

  • TP273
[1] CUNGE J A. Unsteady flow in open channels[M]. Fort Collins, CO: Water Resources Publications,1975:705-761.
[2] 闫旖君,徐建新,陆建红.人民胜利渠灌区多水源循环转化模型研究[J].灌溉排水学报,2017,36(2):52-57. DOI:10.13522/j.cnki.ggps.2017.02.008.
[3] 匡迎春,沈岳,段建南,等. 模糊控制在水稻节水自动灌溉中的应用[J].农业工程学报,2011,27(4):18-21. DOI:10.3969/j.issn.1002-6819.2011.04.004.
[4] 王健,谢南. 基于变论域模糊控制的大豆种植灌溉控制算法[J]. 中国农村水利水电,2017(3):35-40.
[5] 徐宝山,任晓文,闫晓婷. 基于TCC控制模式节水自动化灌溉体系应用[J]. 节水灌溉,2017(2):115-117. DOI:10.3969/j.issn.1007-4929.2017.02.027.
[6] LITRICO X,FROMION V. Modeling and control of hydrosystems[M].London: Springer,2009:17-38.
[7] SEEL T,WERNER C,RAISCHA J,et al.Iterative learning control of a drop foot neuroprosthesis-generating physiological foot motion in paretic gait by automatic feedback control[J]. Control Engineering Practice,2016,48:87-97. DOI:10.1016/j.conengprac.2015.11.007.
[8] LIU Tao,WANG X Z,CHEN Junghui.Robust PID based indirect-type iterative learning control for batch processes with time-varying uncertainties[J]. Journal of Process Control,2014,24(12): 95-106. DOI:10.1016/j.jprocont.2014.07.002.
[9] RABANI A,MADARIAGA J,BOUVIER C,et al.An approach for using iterative learning for controlling the jet penetration depth in abrasive waterjet milling[J].Journal of Manufacturing Processes,2016,22: 99-107. DOI:10.1016/j.jmapro.2016.01.014.
[10] LITRICO X,GEORGES D.Robust continuous-time and discrete-time flow control of a dam-river system:(I)Modelling[J]. Applied Mathematical Modelling,1999,23(11):809-827.DOI: 10.1016/S0307-904X(99)00014-1.
[11] 陆金甫,关治.偏微分方程数值解法[M].2版.北京:清华大学出版社,2004.
[12] 阮新建,杨芳,王长德.渠道运行控制数学模型及系统特性分析[J].灌溉排水,2002,21(1):36-40.DOI:10.13522/j.cnki.ggps.2002.01.010.
[13] 孙明轩,黄宝健.迭代学习控制[M].北京:国防工业出版社,1999.
[14] SUN Mingxuan,GE S S,MAREELS I M Y.Adaptive repetitive learning control of robotic manipulators without the requirement for initial repositioning[J]. IEEE Transactions on Robotics,2006,22(3): 563-568. DOI:10.1109/TRO.2006.870650.
[15] 严求真,孙明轩,李鹤.任意初值非线性不确定系统的迭代学习控制[J].自动化学报,2016,42(4): 545-555. DOI:10.16383/j.aas.2016.c150480.
[16] 阮新建.渠道自动运行现代控制理论模型研究[D].武汉:武汉大学,2002.
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