Control dissolved oxygen in wastewater treatment by interval type-2 fuzzy neural networks

被引：0
|
作者：
Han H. [1 ,2 ]
Liu Z. [1 ,2 ]
Qiao J. [1 ,2 ]
机构：
[1] Faculty of Information Technology, Beijing University of Technology, Beijing
[2] Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing
来源：
Han, Honggui (rechardhan@sina.com) | 2018年 / Materials China卷 / 69期
基金：
中国博士后科学基金; 中国国家自然科学基金;
关键词：
Benchmark simulation model no. 2; Dissolved oxygen; Experimental validation; Interval type-2 fuzzy neural network; Neural network; Process control; Wastewater treatment process;
D O I：
10.11949/j.issn.0438-1157.20171454
中图分类号：
学科分类号：
摘要：
An intelligent controller, based on interval type-2 fuzzy neural networks (IT2FNN) was proposed for controlling dissolved oxygen (DO) concentration in municipal wastewater treatment processes. First, IT2FNN was applied to design a DO concentration controller. Second, an adaptive learning algorithm was used to online adjust controller parameters such that self-adaptability of the IT2FNN-based DO controller could be improved. Finally, IT2FNN-based DO controller was tested in the benchmark simulation model no. 2 (BSM2). The experimental results demonstrate that the controller is able to accurately monitor DO concentration in the fifth unit and maintain excellent control. © All Right Reserved.
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页码：1182 / 1190
页数：8
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