Application of feedforward neural networks for soft sensors in the sugar industry

Abstract

Neural networks have been successfully applied as intelligent sensors for process modeling and control. In this paper, the application of soft sensors in the cane sugar industry is discussed. A neural network is trained on historical data to predict process quality variables so that it can replace the lab-test procedure. An immediate benefit of building intelligent sensors is that the neural network can predict product quality in a timely manner.