Engineering

Volume 2, Issue 10 (October 2010)

ISSN Print: 1947-3931   ISSN Online: 1947-394X

Google-based Impact Factor: 0.66  Citations  

A Fast Predicating of Nutrient Removal Efficiency in Five Steps Sequencing Batch Reactor System Using Fuzzy Logic Control Model

HTML  Download Download as PDF (Size: 1696KB)  PP. 820-831  
DOI: 10.4236/eng.2010.210105    4,660 Downloads   8,688 Views  

Affiliation(s)

.

ABSTRACT

Removal efficiency of COD, NH4-N and PO4-P and NO3-N in five step SBR processes is widely influenced by hydraulic retention time of Anaerobic/Anoxic/Aerobic/Anoxic/Aerobic step of this system where the hydraulic retention time in each step is influence directly on removal efficiency of this system therefore the operator of this system cannot control on this system without experience or a control model. The major objective of this paper is develop a control model (Fuzzy Logic Control Model) based on fuzzy logic rule to predict the maximum removal efficiency of COD,NH4-N,PO4-P and NO3-N and minimize hydraulic retention time in each step of SBR process where the controlled variables was the hydraulic retention times in the Anaerobic/Anoxic/Aerobic/Anoxic/Aerobic step respectively and the output variables was the COD, NH4-N, PO4-P and NO3-N removal efficiency at constant ratio of C/N/P and sludge age. As a results Fuzzy logic if-then rules were used and MIMO Model was built to control COD, NH4-Nand PO4-P and NO3-N removal efficiency based on hydraulic retention time in each tank of five step SBR process where the three dimension results show that the influence of hydraulic residence time at each step of SBR system on removal efficiency COD, NH4-N, PO4-P and NO3-N. Fuzzy control model provide a suitable tool for control and fast predict of Hydraulic residence time effects on biological nutrient removal efficiency in five-step sequencing batch reactor.

Share and Cite:

Abualhail, S. , Naseer, R. , Ashor, A. and Lu, X. (2010) A Fast Predicating of Nutrient Removal Efficiency in Five Steps Sequencing Batch Reactor System Using Fuzzy Logic Control Model. Engineering, 2, 820-831. doi: 10.4236/eng.2010.210105.

Cited by

No relevant information.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.