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作者:

Li, Fei (Li, Fei.) | Yang, Cuili (Yang, Cuili.) | Li, Wenjing (Li, Wenjing.) | Qiao, Junfei (Qiao, Junfei.) (学者:乔俊飞)

收录:

EI PKU CSCD

摘要:

Aiming at the problems of excessive energy consumption (EC) and exceeded seriously effluent quality (EQ) in wastewater treatment control process, an optimal control of wastewater treatment process using a multi-objective uniform distribution NSGAII algorithm (UDNSGAII) was proposed. Firstly, EC and EQ of wastewater treatment are regarded as optimization objectives, and the multi-objective optimal control model is established. Secondly, to obtain the optimal set values of dissolved oxygen (DO) and nitrate nitrogen (NO), and improve the performance of Pareto solution, the individuals which have been clustered are mapped to the hyperplane of the corresponding objective function, then, the diversity of population is increased. In addition, the distribution judgment module and distributed enhancement module are used to improve the distribution of solutions. Finally, PID controller as the bottom controller is used to track the optimal setting value of DO and NO. To test the effectiveness of the proposed algorithm, benchmark simulation model No.1 (BSM1) is used. The results show that the proposed UDNSGAII multi-objective optimization control method can effectively reduce EC of wastewater treatment process while meeting EQ standards. © All Right Reserved.

关键词:

Control engineering Controllers Dissolved oxygen Effluents Effluent treatment Energy utilization Genetic algorithms Multiobjective optimization Process control Reclamation Three term control systems Wastewater treatment Water quality

作者机构:

  • [ 1 ] [Li, Fei]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Li, Fei]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China
  • [ 3 ] [Yang, Cuili]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Yang, Cuili]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China
  • [ 5 ] [Li, Wenjing]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 6 ] [Li, Wenjing]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China
  • [ 7 ] [Qiao, Junfei]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 8 ] [Qiao, Junfei]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China

通讯作者信息:

  • 乔俊飞

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

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来源 :

CIESC Journal

ISSN: 0438-1157

年份: 2019

期: 5

卷: 70

页码: 1868-1878

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 4

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

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