Modeling of Temperature Control System of a Batch Process by Neual Networks

Abstract

This paper considers a modeling method of the temperature control system for a chemical plant which produces polythlene in a batch reactor. In this plant, the reaction in a tank is complex and has many nonlinear factors. Thus, it is difficult to make the model which approximates an output of this plant precisely. It is well-known that neural metworks are useful for many problems in nonlinear systems because of the ability of learning and nonlinear representation. We apply the neural network method to model a temperature control system in this plant. Finally, the simulation results are illustrated to show the effectiveness of the modeling method used here for the temperature control system of a batch reactor.