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Improving the efficiency of a wastewater treatment plant by fuzzy control and neural network
1Cologne University of Applied Sciences, Campus Gummersbach, Faculty of Electrical Engineering Am Sandberg 1, D-51643 Gummersbach, Germany. bongards@gm.fh-koein.de
Abstract:
One of the main problems in operating a wastewater treatment plant is the purification of the excess water from dewatering and pressing of sludge. Because of a high load of organic material and of nitrogen it has to be buffered and treated together with the inflowing wastewater. Different control strategies are discussed. A combination of neural network for predicting outflow values one hour in advance and fuzzy controller for dosing the sludge water are presented. This design allows the construction of a highly non-linear predictive controller adapted to the behaviour of the controlled system with a relatively simple and easy to optimise fuzzy controller. Measurement results of its operation on a municipal wastewater treatment plant of 60,000 inhabitant equivalents are presented and discussed. In several months of operation the system has proved very reliable and robust tool for improving the system's efficiency.
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