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作者:

Han, Honggui (Han, Honggui.) (学者:韩红桂) | Liu, Hongxu (Liu, Hongxu.) | Li, Jiaming (Li, Jiaming.) | Qiao, Junfei (Qiao, Junfei.) (学者:乔俊飞)

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SCIE

摘要:

Wastewater treatment process, including multiple biochemical reactions, is a complex industrial process with strong nonlinearity and time-varying dynamics. It is a challenge to design an effective controller for this kind of process. To solve this problem, a cooperative fuzzy-neural controller is proposed to improve the operation performance of wastewater treatment process in this article. The main advantages of cooperative fuzzy-neural controller contain the following three parts: first, a structure cooperative strategy is developed to adjust the number of fuzzy rules in the controller by coordinating the indexes of similarity and independent contributions. Then, the structure of cooperative fuzzy-neural controller with the balanced redundant degree and efficiency can be adapted to satisfy the different operation conditions of wastewater treatment process. Second, a parameter cooperative strategy is proposed to coordinate the global and local parameters of controller. Then, the parameters can be optimized together to meet the control requirements. Third, the stability of control strategy is given in details. Then, the corresponding stability conditions are shown to guide its application. Finally, the control performance is confirmed on the benchmark simulation model and real wastewater treatment process. The results demonstrate that the proposed cooperative fuzzy-neural controller can achieve superior control precision and low computational burden.

关键词:

Cooperative fuzzy-neural control Fuzzy control Fuzzy neural networks parameter cooperative strategy Process control stability analysis Stability criteria structure cooperative strategy Wastewater Wastewater treatment wastewater treatment process

作者机构:

  • [ 1 ] [Han, Honggui]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Engn Res Ctr Digital Community,Minist Educ,Beijin, Beijing 100124, Peoples R China
  • [ 2 ] [Liu, Hongxu]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Engn Res Ctr Digital Community,Minist Educ,Beijin, Beijing 100124, Peoples R China
  • [ 3 ] [Li, Jiaming]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Engn Res Ctr Digital Community,Minist Educ,Beijin, Beijing 100124, Peoples R China
  • [ 4 ] [Qiao, Junfei]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Engn Res Ctr Digital Community,Minist Educ,Beijin, Beijing 100124, Peoples R China
  • [ 5 ] [Han, Honggui]Beijing Univ Technol, Beijing Lab Urban Mass Transit, Beijing 100124, Peoples R China
  • [ 6 ] [Liu, Hongxu]Beijing Univ Technol, Beijing Lab Urban Mass Transit, Beijing 100124, Peoples R China
  • [ 7 ] [Li, Jiaming]Beijing Univ Technol, Beijing Lab Urban Mass Transit, Beijing 100124, Peoples R China
  • [ 8 ] [Qiao, Junfei]Beijing Univ Technol, Beijing Lab Urban Mass Transit, Beijing 100124, Peoples R China

通讯作者信息:

  • 韩红桂

    [Han, Honggui]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Engn Res Ctr Digital Community,Minist Educ,Beijin, Beijing 100124, Peoples R China;;[Han, Honggui]Beijing Univ Technol, Beijing Lab Urban Mass Transit, Beijing 100124, Peoples R China

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来源 :

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

ISSN: 1551-3203

年份: 2021

期: 9

卷: 17

页码: 5971-5981

1 2 . 3 0 0

JCR@2022

ESI学科: ENGINEERING;

ESI高被引阀值:9

被引次数:

WoS核心集被引频次: 19

SCOPUS被引频次: 36

ESI高被引论文在榜: 0 展开所有

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中文被引频次:

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