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Author:

Qiao, Jun-fei (Qiao, Jun-fei.) (Scholars:乔俊飞) | Han, Guang (Han, Guang.) | Han, Hong-gui (Han, Hong-gui.) (Scholars:韩红桂)

Indexed by:

EI Scopus SCIE

Abstract:

A neural network on-line modeling and controlling method (NNOMC) is proposed in this paper for multi-variable control of wastewater treatment processes (WWTPs). According to the approximating character of the feedforward neural network (FNN), a modeling FNN is proposed to simulate and decouple WWTPs. Then, an FNN controller for multi-variable control of WWTPs is designed. Moreover, the stability of the NNOMC method is proven in a general inference via the limitation of the learning rate of the FNN. Finally, this proposed NNOMC method is used in the international benchmark of WWTPs. The results show the NNOMC method owns both better approximating and controlling performance.

Keyword:

stability multi-variable control decouple Feedforward neural network modeling

Author Community:

  • [ 1 ] [Qiao, Jun-fei]Beijing Univ Technol, Coll Elect & Control Engn, Beijing 100124, Peoples R China
  • [ 2 ] [Han, Guang]Beijing Univ Technol, Coll Elect & Control Engn, Beijing 100124, Peoples R China
  • [ 3 ] [Han, Hong-gui]Beijing Univ Technol, Coll Elect & Control Engn, Beijing 100124, Peoples R China

Reprint Author's Address:

  • 乔俊飞

    [Qiao, Jun-fei]Beijing Univ Technol, Coll Elect & Control Engn, Beijing 100124, Peoples R China

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Source :

ASIAN JOURNAL OF CONTROL

ISSN: 1561-8625

Year: 2014

Issue: 4

Volume: 16

Page: 1213-1223

2 . 4 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:176

JCR Journal Grade:2

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count: 26

SCOPUS Cited Count: 37

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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