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基于模糊神经网络的SBR污水处理控制系统研究
引用本文:欧长劲,吴海列,李军,程园标.基于模糊神经网络的SBR污水处理控制系统研究[J].计算机测量与控制,2006,14(12):1643-1645.
作者姓名:欧长劲  吴海列  李军  程园标
作者单位:浙江工业大学,浙江,杭州,310014
摘    要:序批式活性污泥法(SBR)污水处理过程是一个具有随机性、时变性和耦合性的复杂过程,传统的时间程序控制或流量控制难以获得满意的控制效果;提出了一个具有五层的模糊神经网络控制系统,分析了控制模型与算法,利用神经网络的学习能力来优化模糊逻辑的规则以及比例因子的调整,可实现SBR反应过程的最优控制。通过用MATLAB软件对控制系统进行仿真分析,结果表明系统具有优良的性能。

关 键 词:PID控制  模糊神经网络
文章编号:1671-4598(2006)12-1643-03
收稿时间:2006-04-04
修稿时间:2006-05-10

Study of SBR Control System Based on Fuzzy Neural Network
Ou Changjin,Wu Hailie,Li Jun,Cheng Guobiao.Study of SBR Control System Based on Fuzzy Neural Network[J].Computer Measurement & Control,2006,14(12):1643-1645.
Authors:Ou Changjin  Wu Hailie  Li Jun  Cheng Guobiao
Affiliation:Zhejiang University of Technology, Hangzhou 310014, China
Abstract:Treating sewage water is a very complex process which is random,time-variant and coupling in a Sequencing Batch Reactor(SBR).Traditional control method,such as time programmable control and flow control,cannot improve the effect of the result.This paper presents five layers of fuzzy neural network control system,and the control model and algorithm are described.The study ability of the neural network is used to optimize logical rules and adjust proportional gene,which can reach the optimal control of the SBR reaction.Simulation performed to the control system by MATLAB indicates that its property is excellent.
Keywords:SBR  DO
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