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作者:

Han, Honggui (Han, Honggui.) | Qin, Chenhui (Qin, Chenhui.) | Sun, Haoyuan (Sun, Haoyuan.) | Yang, Hongyan (Yang, Hongyan.) | Qiao, Junfei (Qiao, Junfei.)

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EI Scopus SCIE

摘要:

The phenomenon of sludge bulking, which can be classified as slight or serious abnormal operating conditions according to sludge volume index (SVI), is a widespread problem in wastewater treatment process. In this article, a piecewise sliding-mode control (PSMC) strategy is developed to overcome the adverse effects and furthermore improve the operating performance for wastewater treatment process under different operating conditions of sludge bulking. First, a soft sensing model of SVI based on fuzzy neural network is established. Then, it can online determine the state of sludge and whether sludge bulking has occurred. Second, in view of the specific operating condition of sludge, a piecewise sliding-mode controller is designed. Then, the sludge bulking can be eliminated by regulating the concentration of dissolved oxygen and nitrate nitrogen. Third, the boundary condition of PSMC is evaluated. Then, the stability of the control system is proved on the basis of ensuring the boundary condition of PSMC. Finally, the performance of PSMC is verified in the benchmark simulation platform. The results further demonstrate the effectiveness of the proposed control method.

关键词:

Fuzzy neural networks sludge bulking piecewise sliding-mode control Sliding mode control Multiple operating conditions Nitrogen Microorganisms Process control Recycling Wastewater treatment wastewater treatment process

作者机构:

  • [ 1 ] [Han, Honggui]Beijing Univ Technol, Beijing Artificial Intelligence Inst, Beijing Key Lab Computat Intelligence & Intelligen, Fac Informat Technol,Engn Res Ctr Digital Communit, Beijing 100021, Peoples R China
  • [ 2 ] [Qin, Chenhui]Beijing Univ Technol, Beijing Lab Intelligent Environm Protect, Beijing 10021, Peoples R China

通讯作者信息:

  • [Han, Honggui]Beijing Univ Technol, Beijing Artificial Intelligence Inst, Beijing Key Lab Computat Intelligence & Intelligen, Fac Informat Technol,Engn Res Ctr Digital Communit, Beijing 100021, Peoples R China;;

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来源 :

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

ISSN: 1551-3203

年份: 2023

期: 3

卷: 19

页码: 2876-2885

1 2 . 3 0 0

JCR@2022

ESI学科: ENGINEERING;

ESI高被引阀值:19

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