A neural network, based on bicarbonate monitoring, to control anaerobic digestion

Abstract The use of a neural network simulation for monitoring and controlling an anaerobic digestion process by utilising data from an on-line bicarbonate alkalinity (BA) sensor is presented. The results collected from a series of induced disturbances, in the form of an increase in influent concentration, suggest that the instrument is very sensitive to BA changes and that the neural network is capable of rapid recognition of these disturbances. A scheme for the use of these changes is suggested that would allow on-line control of the digestion process in cases where the wastewater has a low pH buffering capacity.