基于自适应免疫优化的污水处理过程控制

doi:10.16182/j.issn1004731x.joss.21-FZ0821E

系统仿真学报 ›› 2021, Vol. 33 ›› Issue (12): 3012-3020.doi: 10.16182/j.issn1004731x.joss.21-FZ0821E

• 国民经济仿真 • 上一篇

基于自适应免疫优化的污水处理过程控制

李霏^1,2,3, 苏中¹

1.北京信息科技大学自动化学院,北京 100192;
2.北京京新科高端信息产业技术研究院有限公司,北京 100192;
3.北京工业大学信息学部,北京 100124

收稿日期:2021-05-10 修回日期:2021-08-14 出版日期:2021-12-18 发布日期:2022-01-13

Intelligent Control of Wastewater Treatment Processes Based on Adaptive Immune Optimization

Li Fei^1,2,3, Su Zhong¹

1. School of Automation, Beijing Information Science & Technology University, Beijing 100192, China;
2. Beijing Jingxinke High-end Information Industry Technology Research Institute Co. Ltd, Beijing 100192, China;
3. Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China

Received:2021-05-10 Revised:2021-08-14 Online:2021-12-18 Published:2022-01-13
About author:Li Fei(1985-), women, Ph.D, engineer, research area: neural networks, intelligent systems, Multi- objective optimization algorithm, and process control systems. E-mail: lifei@bistu.edu.cn
Supported by:
National Key Research and Development Program (2020YFC1511702); National Natural Science Foundation (61771059, 619710480, 62003185); Beijing Science and Technology Project (Z191100001419012)

摘要/Abstract

摘要： 为解决污水处理过程控制中能耗过高、出水水质差的问题,提出一种基于自适应免疫优化(AIOIC)的智能控制系统。设计分层控制策略,采用基于奇异值分解的快速在线自组织模糊神经网络(SVDFNN)构建污水处理能耗和出水水质模型。采用自适应混合免疫优化算法,获得最佳的溶解氧和硝态氮设定值。利用底层的自组织递归模糊神经网络控制器跟踪该优化设定值。结果表明：所提出的免疫优化智能控制策略不仅能满足出水水质标准,而且能显著降低污水处理能耗。

关键词: 污水处理, 自组织模糊神经网络, 免疫多目标优化, 智能控制系统, 能耗

Abstract: In order to solve the problems of excessive energy consumption and excessive effluent quality in wastewater treatment process control, an intelligent control system based on adaptive immune optimization (AIOIC) is proposed. A hierarchical control strategy is designed, and a fast online self-organizing fuzzy neural network based on singular value decomposition (SVDFNN) is used to construct the mathematical model of wastewater treatment energy consumption and effluent quality. In order to obtain the optimal set values of dissolved oxygen and nitrate nitrogen, an adaptive hybrid evolutionary immune optimization algorithm is designed. The self-organizing recursive fuzzy neural network controller is used to track this optimal set points at the bottom layer. The results show that the proposed immune optimization intelligent control strategy can not only meet the effluent quality standard, but also significantly reduce the energy consumption of wastewater treatment process.

Key words: wastewater treatment process, self-organization fuzzy neural network, immune multi-objective optimization, intelligent control system, energy consumption

中图分类号:

李霏, 苏中. 基于自适应免疫优化的污水处理过程控制[J]. 系统仿真学报, 2021, 33(12): 3012-3020.

Li Fei, Su Zhong. Intelligent Control of Wastewater Treatment Processes Based on Adaptive Immune Optimization[J]. Journal of System Simulation, 2021, 33(12): 3012-3020.

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基于自适应免疫优化的污水处理过程控制

Intelligent Control of Wastewater Treatment Processes Based on Adaptive Immune Optimization

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