Research on the Application of PID Control with Neural Network and Parameter Adjustment Method of PID Controller

PID control is a kind of control method based on the error of the system, using the proportion, integral and differential to calculate the control quantity and adjust the system error. The PID controller is widely used in various fields of industrial control because it does not need to establish the accurate mathematical model of the system. However, the three parameter values of classical PID control methods are usually artificially assigned, and artificial assignment often depends on experience, so the control efficiency is relatively low. In this paper, an accelerating BP neural network based on momentum constant is used to achieve the self-adjustment of PID controller parameters, and the method is applied to the control system. The simulation experiment shows that using the method of accelerating BP neural network proposed in this paper to adjust the parameters of PID controller has faster convergence ability and can realize the fast approximation function of the system. The method of using intelligent algorithm to adjust the parameters of PID control is widely used in various fields of industrial control. In this paper the commonly used PID controller parameter tuning methods are compared.