Neural Network Modelling for Heat Exchanger

The controlling of heat exchanger using conventional PID controller always face the
problem of having limiting performance due to unpredictable unsteady state thermal
behavior of heat exchangers. In recent decades, the applications of neural network for
thermal analysis of heat exchangers have been extensively studies by great amount of
researchers and institutions. The non-linear characteristic of neural network is deemed
to possess great potential to accurately predict heat exchangers performance. In this
paper, multilayer feedforward network has been chosen as the base network
architecture to construct a neural network model for heat exchanger.