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Author:

Li, San-Yi (Li, San-Yi.) | Qiao, Jun-Fei (Qiao, Jun-Fei.) (Scholars:乔俊飞) | Li, Wen-Jing (Li, Wen-Jing.) | Gu, Ke (Gu, Ke.) (Scholars:顾锞)

Indexed by:

EI Scopus PKU CSCD

Abstract:

In order to inhibit the peak of ammonia nitrogen (SNH,e) and total nitrogen (SNtot,e) concentrations in effluent and reduce energy consumption, we present in this paper a decision and optimization control method. Firstly, we establish the prediction models of SNH,e and SNtot,e with neural network. Secondly, we optimize the set points of dissolved oxygen concentration and nitrate nitrogen concentration with multiobjective evolutionary algorithm. Lastly, select control strategy (optimal control strategy or inhibitory control strategy) based on the outcome of prediction models. Evaluation is carried out with the Benchmark Simulation Model No.1. The results show that the proposed method restrains the peaks of SNH,e and SNtot,e effectively while the percentages of time of SNH,e and SNtot,e violations are less than those of the compared inhibitory control methods, and that the energy consumption using the proposed method is less than that using the counterpart inhibitory control method significantly. Copyright © 2018 Acta Automatica Sinica. All rights reserved.

Keyword:

Evolutionary algorithms Forecasting Wastewater treatment Effluents Optimal control systems Predictive analytics Ammonia Dissolved oxygen Nitrogen Sewage treatment plants Energy utilization

Author Community:

  • [ 1 ] [Li, San-Yi]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Li, San-Yi]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China
  • [ 3 ] [Qiao, Jun-Fei]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Qiao, Jun-Fei]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China
  • [ 5 ] [Li, Wen-Jing]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 6 ] [Li, Wen-Jing]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China
  • [ 7 ] [Gu, Ke]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 8 ] [Gu, Ke]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China

Reprint Author's Address:

  • 乔俊飞

    [qiao, jun-fei]faculty of information technology, beijing university of technology, beijing; 100124, china;;[qiao, jun-fei]beijing key laboratory of computational intelligence and intelligent system, beijing; 100124, china

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Source :

Acta Automatica Sinica

ISSN: 0254-4156

Year: 2018

Issue: 12

Volume: 44

Page: 2198-2209

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 12

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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