Temperature control in a batch process by neural networks

This paper considers a temperature control scheme for a chemical plant on the basis of experimental results. The target plant produces poleythlene in a batch reactor. Here the reaction in a tank is complex and has many nonlinear factors. The temperature control is realized by valves manipulation. Since the valve control has been performed by using a conventional PID controller, it generally needs much effort and time to tune the PID gains. Thus in the production field, a new control system is needed to tune the PID gains without operator's decision under various conditions of the plant. For that purpose, we use a self-tuning neuro-PID control method which has the characteristic of tuning PID gains automatically by neural networks. From the experiment results, we show the effectiveness of the proposal algorithm to improve the control performance of the temperature in the batch reactor.