Application of Single Neuron Adaptive PID Controller in Flow Control System

Oxide concentration at reactor inlet is one of the most important factor effecting the quality of ethylene oxide concentration. A control method with adaptive PID of single neuron is propose using the parameter self-learning with adaptive PID controller of single neuron for the oxide flow control system. The simulation results show that this design scheme has a better dynamic performance than traditional PID scheme to verify the feasibility of this method.