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

HAN Honggui; LIU Zheng; QIAO Junfei

doi:10.11949/j.issn.0438-1157.20171454

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

更新时间：2025-12-10

- Control dissolved oxygen in wastewater treatment by interval type-2 fuzzy neural networks
- CIESC Journal Issue 3, Pages: 1182-1190(2018)
- 作者机构：
  
  1. 北京工业大学信息学部,北京,100124
  2. 计算智能与智能系统北京市重点实验室,北京,100124
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20171454
  CLC： P173
- Online First：05 March 2018，
  
  Published：05 March 2018
- 稿件说明：
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HAN Honggui, LIU Zheng, QIAO Junfei. Control dissolved oxygen in wastewater treatment by interval type-2 fuzzy neural networks[J]. CIESC Journal, 2018, (3): 1182-1190.
DOI：

HAN Honggui, LIU Zheng, QIAO Junfei. Control dissolved oxygen in wastewater treatment by interval type-2 fuzzy neural networks[J]. CIESC Journal, 2018, (3): 1182-1190. DOI： 10.11949/j.issn.0438-1157.20171454.

摘要

针对城市污水处理过程溶解氧浓度难以精确控制的问题，提出了一种基于区间二型模糊神经网络（interval type-2 fuzzy neural networks，IT2FNN）的溶解氧浓度控制方法。先将IT2FNN应用在城市污水处理过程溶解氧浓度控制器的设计，获得了一种IT2FNN溶解氧浓度控制器。后采用自适应学习算法在线调整控制器的参数，提高了控制器的自适应能力。最后将提出的IT2FNN溶解氧浓度控制器应用于基准仿真2号模型（benchmark simulation model no.2，BSM2）平台，结果表明，IT2FNN控制器能够实现第5分区溶解氧浓度精确控制，具有较好的控制效果。

Abstract

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.

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