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《Journal of Irrigation and Drainage》 2007-06
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Study on Canal System Operation Controlled by PID Neural Network

YAO Xiong,WANG Chang-de,DING Zhi-liang(State Key Laboratory of Water Resources and Hydropower Engineering Science,Wuhan University,Wuhan 430072,China)  
Canal system has the characteristics of non-linearity,long time lag of dynamic response and time variation.Neural network is just good at dealing with nonlinear and uncertain systems,so a water feedback controller based on PID neural network was developed.It has both the merits of PID rule and neural network such as simpleness and high reliability,self-learning and selfadaptive ability.Furthermore,the control parameters can be integrated not depending on the canal mathematical model and can be adjusted according to the real-time information of the canal system.Based on canal hydraulics characteristics,a mathematical model of canal system was constituted and the computer simulation was carried out.The simulation results prove that the performance of canal system operation controlled by PID neural network control is better than that controlled by conventional PID control.
【Fund】: 国家863计划课题(2001AA242111)
【CateGory Index】: TP183
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【Co-citations】
Chinese Journal Full-text Database 10 Hits
1 LIU Qingfeng,YIN Jiuren(Institute of Fundamental Mechanics & Material Engineering,Xiangtan University,Xiangtan411105,China);Status quo and prospects of the neural network intelligence and ability diagnosis in concrete structure[J];Sichuan Building Science;2007-01
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5 Liu Hong Ren Kun Chen Wenkai (Beijing University of Technolog,Beijing 100022,China);Neural Network Based Comparative Study of Genetic and BP Training Algorithms[J];Journal of Beijing Polytechnic College;2008-02
6 Pei Zhongcai Yin Li Wang Zhanlin(School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China);Simulating turntable control system with neural network[J];Journal of Beijing University of Aeronautics and Astronautics;2005-09
7 Dong Weijie (School of Automation Science and Electrical Engineering,Beijing University of Aeronautics and Astronautics,Beijing 100083,China)Liu Changhua(Base of Flight Safety Civil Aviation Flight University of China,Chengdu 610000,China)Song Hua(School of Automation Science and Electrical Engineering,Beijing University of Aeronautics and Astronautics,Beijing 100083,China);Human perceive system of simulative aircraft based on PIDNN[J];Journal of Beijing University of Aeronautics and Astronautics;2008-02
8 Hu Yuling(School of Electricity and Information Engineering,Beijing 100044);Research on Identification of Dynamic System Based on T-S Recurrent Fuzzy Neural Network[J];Journal of Beijing Institute of Civil Engineering and Architecture;2006-03
9 LI Wei-min (Dept.Electronics & Elect.Engn.,Baoji Univ.Arts & Sci.,Baoji 721007,Shaanxi,China);A novel composite artificial neuron net controller[J];Journal of Baoji University of Arts and Sciences(Natural Science Edition);2008-01
10 ZHANG Li-jun,XU Jia(Department of Electronic Information,Beijing Institute of Graphic Communication,Beijing 102600,China);Study and Discussion of Artificial Neuron Circuit Structure[J];Journal of Beijing Institute of Graphic Communication;2006-04
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1 Liu Yong, Zhao Zixian(College of Sciences and Technology, Inner Mongolia University, Hohhot 010021);Smith-PID Control Based on RBF NN Tuning and Its Application[A];[C];2005
2 Zhao Guo-xin (Intelligent Department,Automation Research and Design Institute of Metallurgical Industry,Beijing,100071);Intelligent Control System for Coke Oven[A];[C];2008
3 ;冷轧机液压AGC神经网络自适应PID控制的研究[A];[C];2008
4 Liu Baoquan Liu Jun Lian Fayong (Cold Roll Workshop of Ansteel Co.,Ltd.,Anshan,114021);Study on Neural Network Adaptive PID Control of Hydraulic AGC System Cold Rolling Mill[A];[C];2009
5 ZhangHong WangJianming (Harbin Institute of Technology(Weihai),Weihai 264200 China);The application of Neural Network Predictive Control Technology in VAV Air Conditioning Room[A];[C];2008
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