Kern, Peter and Wolf, Christian and Bongards, Michael and Oyetoyan, Tosin Daniel and McLoone, Sean F. (2011) Self-Organizing Map based operating regime estimation for state based control of Wastewater Treatment Plants. In: Third International Conference of Soft Computing and Pattern Recognition (SocPaR 2011), 14-16 October 2011, Dalian, China.

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Abstract

An optimal control of wastewater treatment plants (WWTP) has to account for changes in the bio-chemical state of the bioreactors. As many process variables of a WWTP are not measurable online, the development of an efficient control strategy is one of the greatest challenges in the optimization of WWTP operation. This paper presents an approach, which combines the use of Self-Organizing Maps (SOM) and a clustering algorithm to identify operational patterns in WWTP process data. These patterns provide a basis for the optimization of controller set points that are well suited for the previously identified operation regimes of the plant. The optimization is performed using Genetic Algorithms. This approach was developed, tested and validated on a simulation model based on the Activated Sludge Model No.1 (ASM1). The results of this state-based control indicate that the presented methodology is a promising and useful control strategy that is definitely able to address the distinctive energy and effluent limit challenges faced by WWTP operators.

Item Type:	Conference or Workshop Item (Paper)
Keywords:	Wastewater Treatment; State based Control; Self Organizing Maps; Clustering; Optimization; Genetic Algorithm;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering
Item ID:	3651
Depositing User:	Sean McLoone
Date Deposited:	08 May 2012 15:32
Refereed:	Yes
URI:
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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