Machine Learning and Intelligent Communications. 4th International Conference, MLICOM 2019, Nanjing, China, August 24–25, 2019, Proceedings

Research Article

Sewage Treatment Control Method Based on Genetic-SOFNN

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  • @INPROCEEDINGS{10.1007/978-3-030-32388-2_53,
        author={Zhuang Yang and Cuili Yang and Junfei Qiao},
        title={Sewage Treatment Control Method Based on Genetic-SOFNN},
        proceedings={Machine Learning and Intelligent Communications. 4th International Conference, MLICOM 2019, Nanjing, China, August 24--25, 2019, Proceedings},
        proceedings_a={MLICOM},
        year={2019},
        month={10},
        keywords={Sewage treatment Fuzzy neural network Tracking control Projection gradient learning},
        doi={10.1007/978-3-030-32388-2_53}
    }
    
  • Zhuang Yang
    Cuili Yang
    Junfei Qiao
    Year: 2019
    Sewage Treatment Control Method Based on Genetic-SOFNN
    MLICOM
    Springer
    DOI: 10.1007/978-3-030-32388-2_53
Zhuang Yang1,*, Cuili Yang1,*, Junfei Qiao1,*
  • 1: Beijing University of Technology
*Contact email: 892836748@qq.com, clyang5@bjut.edu.cn, junfeiq@bjut.edu.cn

Abstract

In the sewage treatment process, the dissolved oxygen concentration is a very important control target, but it is difficult to be controlled. To solve this problem, a self-organizing fuzzy neural network controller based on genetic ideas (G-SOFNN) is proposed. In the controller structure reduction process, the deleted neuron information is merged with the remaining neurons to reduce the interference set. During the controller structure increasing phase, the information of new neurons is initialized to avoid overlapping of information. Then, the controller parameters are trained by the projection algorithm to improve the control precision. Experiments illustrate that the proposed method can accurately control the concentration of dissolved oxygen in the sewage treatment process.