CIESC Journal ›› 2020, Vol. 71 ›› Issue (3): 1217-1225.DOI: 10.11949/0438-1157.20191514

• Process system engineering • Previous Articles     Next Articles

FNN-based process control for biochemical phosphorus in WWTP

Lu ZHANG1,2,3,Jiacheng ZHANG1,2,3,Honggui HAN1,2,3(),Junfei QIAO1,2   

  1. 1.Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
    2.Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing 100124, China
    3.Engineering Research Center of Digital Community, Ministry of Education, Beijing 100124, China
  • Received:2019-12-16 Revised:2019-12-24 Online:2020-03-05 Published:2020-03-05
  • Contact: Honggui HAN

基于模糊神经网络的污水处理生化除磷过程控制

张璐1,2,3,张嘉成1,2,3,韩红桂1,2,3(),乔俊飞1,2   

  1. 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
    3.数字社区教育部工程研究中心,北京 100124
  • 通讯作者: 韩红桂
  • 基金资助:
    国家重点研发计划项目(2018YFC1900800-05);国家自然科学基金项目(61890930-5)

Abstract:

To make the effluent total phosphorus reach the real-time standard in wastewater treatment process (WWTP), an effluent total phosphorus control strategy, based on fuzzy neural network (FNN), is proposed to control the biochemical phosphorus in this paper. First, the manipulated variables, based on the mechanism analysis of biochemical phosphorus removal process, were considered as the external carbon (EC) and dissolved oxygen (DO) transfer coefficient. Second, an FNN-based process controller was designed to control the effluent total phosphorus. And a gradient descent algorithm was applied to adjust the parameters of controller. Finally, the proposed FNN-based process controller was tested on the benchmark simulation model No. 1 (BSM1) to evaluate its effectiveness. The results demonstrated that the proposed FNN-based process controller can guarantee the standard discharge of effluent total phosphorus. The results show that the FNN-based effluent total phosphorus controller can ensure that the total effluent total phosphorus is discharged and has a good control effect.

Key words: wastewater treatment process, phosphorus removal, fuzzy neural network, process control

摘要:

针对污水处理生化除磷过程中出水总磷难以实时达标的问题,提出了一种基于模糊神经网络(fuzzy neural network,FNN)的出水总磷控制方法。首先,通过分析污水处理生化除磷机理,确定了控制器的操作变量为生化反应池第五分区外部碳源(external carbon, EC)与溶解氧(dissolved oxygen, DO)传递系数。其次,设计了一种基于FNN的出水总磷控制器,采用梯度下降算法更新控制器参数;最后,将基于FNN的出水总磷控制器应用于污水处理过程基准仿真平台(benchmark simulation model No.1,BSM1),实验结果表明,基于FNN的出水总磷控制器能够保证出水总磷的达标排放,具有较好的控制效果。

关键词: 污水处理过程, 生化除磷, 模糊神经网络, 过程控制

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