Performance Analysis of Heat Exchanger System Using Deep Learning Controller

Abstract

Conventional PID controllers have utilised in most of the process industries. Despite being the most used controller, the traditional PID controller suffers from several disadvantages. Due to rapid development in the field of the process control system, various controllers have been developed that try to overcome the limitations of the PID controller. In this paper, a heat exchanger system has been simulated, and the generated data has been used to train a deep learning-based controller using Backpropagation. The obtained results are compared with the conventional controller on several metrics, including time response, performance indices, frequency response etc. The proposed model outperforms the conventional controller on all the evaluation metrics.