Automatic Control Synthesis Based on Integrated Neuro-Controller

Abstract

The purpose of this study is to develop a multi-functional automated process controller for use in a synthesis system of chemical reactions. Chemical reactions can be very complex, making it difficult to control the reaction temperature. In this research, a neural network is proposed for controlling the temperature of the reaction. First, the system dynamics are identified from real time experimental data using a neural network. Next a neural network controller is constructed to regulate the temperature of the chemical reaction, then its effectiveness is tested through simulations and experiments. Finally a neural network diagnostic system is proposed in the event of, machine trouble or human error. A new type of chemical conversion estimation is also proposed from these results, and it is verified that it can efficiently control the chemical reaction using developed the AI process controller.