DEVELOPMENT OF ANN MODEL FOR NON-LINEAR DRYING PROCESS

Abstract

ABSTRACT This paper presents an application of artificial neural network (ANN) technique to develop a model representing the non-linear drying process. The air heat plant (AHP), an important component in drying process is fabricated and used for building the ANN model. An optimal feed forward neural network topology is identified for the air heating system set-up. The training sets are obtained from experimental data. Back propogation algorithm with momentum factor is used for training. The results show that the back propogation ANN can learn the functional mapping between input and output. The advantages of ANN model developed for AHP is highlighted. The developed model can be used for control purposes.