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Author:

Fu, Wen-Tao (Fu, Wen-Tao.) | Qiao, Jun-Fei (Qiao, Jun-Fei.) (Scholars:乔俊飞) | Han, Gai-Tang (Han, Gai-Tang.) | Meng, Xi (Meng, Xi.)

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EI Scopus

Abstract:

In this paper, a novel kind of the dissolved oxygen (DO) concentration control system was proposed based on the T-S fuzzy neural network. The proposed T-S fuzzy neural network controller was used to control the DO concentration in the Benchmark Simulation Model No.1 (BSM1) wastewater treatment platform. The parameters of the neural network were adjusted online through the error back propagation algorithm to get the minimum error. By adjusting the learning rate online, the convergence speed of the system was accelerated, and then the DO concentration in the wastewater treatment system was controlled fast and efficiently in real-time. Compared with BP and PID controllers through the digital simulation, the results showed that the control effect of the DO concentration based on T-S fuzzy neural network control system was better. Besides, the test results under three kinds of weather condition showed that better adaptability and robustness were also gained in this control system. © 2015 IEEE.

Keyword:

Controllers Simulation platform Reclamation Dissolved oxygen Fuzzy inference Fuzzy logic Three term control systems Wastewater treatment Fuzzy neural networks Dissolution Backpropagation algorithms Biochemical oxygen demand

Author Community:

  • [ 1 ] [Fu, Wen-Tao]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 2 ] [Qiao, Jun-Fei]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 3 ] [Han, Gai-Tang]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 4 ] [Meng, Xi]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China

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Source :

Year: 2015

Volume: 2015-September

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 8

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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