[1]QIAO Junfei,PANG Zefang,HAN Honggui.Neural network optimal control for wastewater treatment processbased on APSO[J].CAAI Transactions on Intelligent Systems,2012,7(5):429-436.
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Neural network optimal control for wastewater treatment processbased on APSO

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 7 Number of periods: 2012 5 Page number: 429-436 Column: 学术论文—智能系统 Public date: 2012-10-25
Title:
Neural network optimal control for wastewater treatment processbased on APSO
Author(s):
QIAO Junfei;  PANG Zefang;  HAN Honggui 
College of Electronic and Control Engineering, Beijing University of Technology, Beijing 100124, China
Keywords:
wastewater treatment;  intelligent control;  optimal control;  particle swarm optimzation;  neural network
CLC:
TP18
DOI:
-
Abstract:
Due to the high energy consumption of activated sludge wastewater treatment process, a new intelligent optimal control system is designed in this paper by considering the effluent quality and the relationship between the biochemical reaction parameters. This control system is used for the benchmark simulation model (BSM1) proposed by the International Water Association (IWA). The APSO is utilized to optimize the dissolved oxygen and MLSS levels in the fifth compartment and the nitrate level in the second anoxic tank. Meanwhile, the outputs of BSM1 are predicted by the neural network, and the energy consumption is cut down whthin the effluent water quality standarts. The simulation results show that, comparing to the clooseloop control strategy, the totle energy consumption of this proposed optimal control system is lowered by 4.614%, the neural network optimal control strategy can significantly reduce the energy consumption of activated sludge wastewater treatment process.
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