Journal of System Simulation
Abstract
Abstract: In order to solve the problems of excessive energy consumption and excessive effluent quality in wastewater treatment process control, an intelligent control system based on adaptive immune optimization (AIOIC) is proposed. A hierarchical control strategy is designed, and a fast online self-organizing fuzzy neural network based on singular value decomposition (SVDFNN) is used to construct the mathematical model of wastewater treatment energy consumption and effluent quality. In order to obtain the optimal set values of dissolved oxygen and nitrate nitrogen, an adaptive hybrid evolutionary immune optimization algorithm is designed. The self-organizing recursive fuzzy neural network controller is used to track this optimal set points at the bottom layer. The results show that the proposed immune optimization intelligent control strategy can not only meet the effluent quality standard, but also significantly reduce the energy consumption of wastewater treatment process.
Recommended Citation
Fei, Li and Zhong, Su
(2022)
"Intelligent Control of Wastewater Treatment Processes Based on Adaptive Immune Optimization,"
Journal of System Simulation: Vol. 33:
Iss.
12, Article 26.
DOI: 10.16182/j.issn1004731x.joss.21-FZ0821E
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol33/iss12/26
First Page
3012
Revised Date
2021-08-14
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.21-FZ0821E
Last Page
3020
CLC
TP273+.4A;TP391
Recommended Citation
Li Fei, Su Zhong. Intelligent Control of Wastewater Treatment Processes Based on Adaptive Immune Optimization[J]. Journal of System Simulation, 2021, 33(12): 3012-3020.
DOI
10.16182/j.issn1004731x.joss.21-FZ0821E
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