| Neural-fuzzy control system application for monitoring process response and control of anaerobic hybrid reactor in wastewater treatment and biogas production. | |
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MedLine Citation:
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PMID: 21462705 Owner: NLM Status: In-Process |
Abstract/OtherAbstract:
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Based on the developed neural-fuzzy control system for anaerobic hybrid reactor (AHR) in wastewater treatment and biogas production, the neural network with backpropagation algorithm for prediction of the variables pH, alkalinity (Alk) and total volatile acids (TVA) at present day time t was used as input data for the fuzzy logic to calculate the influent feed flow rate that was applied to control and monitor the process response at different operations in the initial, overload influent feeding and the recovery phases. In all three phases, this neural-fuzzy control system showed great potential to control AHR in high stability and performance and quick response. Although in the overloading operation phase II with two fold calculating influent flow rate together with a two fold organic loading rate (OLR), this control system had rapid response and was sensitive to the intended overload. When the influent feeding rate was followed by the calculation of control system in the initial operation phase I and the recovery operation phase III, it was found that the neural-fuzzy control system application was capable of controlling the AHR in a good manner with the pH close to 7, TVA/Alk < 0.4 and COD removal > 80% with biogas and methane yields at 0.45 and 0.30 m3/kg COD removed. |
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Authors:
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Chaiwat Waewsak; Annop Nopharatana; Pawinee Chaiprasert |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Journal of environmental sciences (China) Volume: 22 ISSN: 1001-0742 ISO Abbreviation: J Environ Sci (China) Publication Date: 2010 |
Date Detail:
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Created Date: 2011-04-05 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 100967627 Medline TA: J Environ Sci (China) Country: Netherlands |
Other Details:
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Languages: eng Pagination: 1883-90 Citation Subset: IM |
Affiliation:
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Division of Biotechnology, School of Bioresources and Technology, King Mongkut's University of Technology Thonburi, Thakam, Bangkhuntien, Bangkok 10150, Thailand. xmay29@yahoo.com |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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