[1]乔俊飞,王莉莉,韩红桂.基于ESN的污水处理过程优化控制[J].智能系统学报编辑部,2015,10(6):831-837.[doi:10.11992/tis.201401009]
 QIAO Junfei,WANG Lili,HAN Honggui.Optimal control for wastewater treatment process based on ESN neural network[J].CAAI Transactions on Intelligent Systems,2015,10(6):831-837.[doi:10.11992/tis.201401009]
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《智能系统学报》编辑部[ISSN:1673-4785/CN:23-1538/TP]

卷:
第10卷
期数:
2015年6期
页码:
831-837
栏目:
出版日期:
2015-12-25

文章信息/Info

Title:
Optimal control for wastewater treatment process based on ESN neural network
作者:
乔俊飞 王莉莉 韩红桂
北京工业大学电子信息与控制工程学院, 北京 100124
Author(s):
QIAO Junfei WANG Lili HAN Honggui
College of Electronic and Control Engineering, Beijing University of Technology, Beijing 100124, China
关键词:
污水处理过程优化控制状态回声网络性能指标预测模型基准仿真模型
Keywords:
wastewater treatment processoptimal controlecho state networkperformance prediction modelbenchmark simulation model
分类号:
TP18
DOI:
10.11992/tis.201401009
摘要:
针对污水处理过程能耗过高的问题,提出了一种基于状态回声网络(ESN)的在线优化控制方法。建立了污水处理过程预测模型,实现性能指标的预测;根据系统的状态以及预测的性能指标,采用ESN实时优化控制变量的设定值;将优化后的设定值传送给底层控制器进行跟踪控制。将ESN优化控制方法在污水处理过程基准仿真模型(BSM1)上进行了验证,实验结果表明,该方法不但能够满足出水水质的要求,而且降低了污水处理过程运行成本。
Abstract:
To address the problem of the high-energy consumption in wastewater treatment processes, we propose an online optimal control method based on an echo state network(ESN). This method has three main steps. First, we develop a performance prediction model of the wastewater treatment process. Second, based on the system state and the predicted performance index, we optimize the set point of the control variable using the ESN in real time. Then we transfer the optimized set point to the underlying controller for tracking control. This ESN-based online optimal control method is carried out using the benchmark simulation model 1(BSM1). The simulation results show that the proposed method can not only meet the effluent quality requirements, but also efficiently reduce the operation costs of the wastewater treatment process.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2014-01-01;改回日期:。
基金项目:国家自然科学基金重点基金资助项目(61533002);国家自然科学基金杰出青年基金资助项目(61225016);中国博士后科学基金一等资助项目(2014M550017);北京市教育委员会科研计划资助项目(KZ201410005002,km201410005001);高等学校博士学科点专项科研基金资助项目(20131103110016).
作者简介:乔俊飞,男,1968年生,教授,博士生导师,教育部长江学者特聘教授,国家杰出青年基金获得者,北京市精品课程负责人。主要研究方向为智能信息处理、智能优化控制。近5年发表学术论文近70篇,被SCI检索20余篇。教育部科技进步奖一等奖和北京市科学技术奖三等奖各1项,获得授权国家发明专利12项。王莉莉,女,1987年生,硕士研究生,主要研究方向为污水处理智能优化控制。韩红桂,男,1983年生,教授,博士生导师,先后入选香江学者计划,北京市科技新星计划。主要研究方向为污水处理过程建模、优化与控制。近5年来,发表学术论文30余篇,其中SCI检索20余篇。参与3本专著编写,申请国家发明专利20项(其中授权13项)。
通讯作者:韩红桂.E-mail:rechardhan@sina.com.
更新日期/Last Update: 1900-01-01