FNN-based process control for biochemical phosphorus in WWTP - Details

Author：

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

Indexed by：

EI Scopus CSCD

Abstract：

To　make　the　effluent　total　phosphorus　reach　the　real-time　standard　in　wastewater　treatment　process　(WWTP),　an　effluent　total　phosphorus　control　strategy,　based　on　fuzzy　neural　network　(FNN),　is　proposed　to　control　the　biochemical　phosphorus　in　this　paper.　First,　the　manipulated　variables,　based　on　the　mechanism　analysis　of　biochemical　phosphorus　removal　process,　were　considered　as　the　external　carbon　(EC)　and　dissolved　oxygen　(DO)　transfer　coefficient.　Second,　an　FNN-based　process　controller　was　designed　to　control　the　effluent　total　phosphorus.　And　a　gradient　descent　algorithm　was　applied　to　adjust　the　parameters　of　controller.　Finally,　the　proposed　FNN-based　process　controller　was　tested　on　the　benchmark　simulation　model　No.　1　(BSM1)　to　evaluate　its　effectiveness.　The　results　demonstrated　that　the　proposed　FNN-based　process　controller　can　guarantee　the　standard　discharge　of　effluent　total　phosphorus.　The　results　show　that　the　FNN-based　effluent　total　phosphorus　controller　can　ensure　that　the　total　effluent　total　phosphorus　is　discharged　and　has　a　good　control　effect.　©　All　Right　Reserved.

Keyword：

Wastewater treatment Frequency standards Effluents Effluent treatment Fuzzy neural networks Gradient methods Phosphorus Dissolved oxygen Process control Controllers

Author Community：

[ 1 ] [Zhang, Lu]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
[ 2 ] [Zhang, Lu]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China
[ 3 ] [Zhang, Lu]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
[ 4 ] [Zhang, Jiacheng]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
[ 5 ] [Zhang, Jiacheng]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China
[ 6 ] [Zhang, Jiacheng]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
[ 7 ] [Han, Honggui]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
[ 8 ] [Han, Honggui]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China
[ 9 ] [Han, Honggui]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
[ 10 ] [Qiao, Junfei]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
[ 11 ] [Qiao, Junfei]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China

Reprint Author's Address：

韩红桂
[han, honggui]beijing key laboratory of computational intelligence and intelligent system, beijing; 100124, china;;[han, honggui]engineering research center of digital community, ministry of education, beijing; 100124, china;;[han, honggui]faculty of information technology, beijing university of technology, beijing; 100124, china

Email：

rechardhan@sina.com

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