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Author:

Han, Honggui (Han, Honggui.) (Scholars:韩红桂) | Zhang, Lu (Zhang, Lu.) | Qiao, Junfei (Qiao, Junfei.) (Scholars:乔俊飞)

Indexed by:

EI PKU CSCD

Abstract:

To meet effluent quality (EQ) standard and reduce energy consumption (EC) of wastewater treatment process (WWTP), a multi-objective optimal control method was developed based on multi-objective particle swarm optimization (MOPSO). First, EC and EQ models from adaptive regressive kernel functions were established by analysis of operation data. Then, MOPSO was designed to optimize EC and EQ models and to reach optimal set-points of dissolved oxygen (SO) and nitrate (SNO) simultaneously. Finally, PID controller was used to trace the optimal set-points of SO and SNO so as to achieve multi-objective optimal control of WWTP. The experimental results from Benchmark Simulation Model 1 (BSM1) for wastewater treatment demonstrated that the proposed multi-objective optimal control method could assuredly meet effluent quality standard as well as effectively reduce energy consumption. © All Right Reserved.

Keyword:

Dissolved oxygen Particle swarm optimization (PSO) Water quality Three term control systems Wastewater treatment Reclamation Effluent treatment Effluents Benchmarking Energy utilization Quality control Multiobjective optimization

Author Community:

  • [ 1 ] [Han, Honggui]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Zhang, Lu]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Qiao, Junfei]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China

Reprint Author's Address:

  • 韩红桂

    [han, honggui]faculty of information technology, beijing university of technology, beijing; 100124, china

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Source :

CIESC Journal

ISSN: 0438-1157

Year: 2017

Issue: 4

Volume: 68

Page: 1474-1481

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: 9

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