PID Controller Based Neural Networks With Applications

The PID controller is simple in structure, strong in robustness, and can be understood easily. Nevertheless, neural networks have great capability in solving complex mathematical problems since they have been proven to approximate any continuous function as accurately as possible. Hence, it has received considerable attention in the field of process control. Taking the advantage of neural network and applying it to controller design which PID parameters are adjusted on-line for highly nonlinear system, which can improve controller performance. So the research of PID control based on neural network is significant in either theory or application.Based on the analyzing capability of the classical control theory and the character of the neural network control, this paper combines the traditional PID control and the neural network control, this paper explicates the significant position for traditional process control. Subsequently, this paper designs an on-line self-tuning PID controller based on the instantaneous linearization neural network, discusses and simulates two kinds of PID algorithm based on neural network. What's more, an on-line updated PID algorithm is proposed, and one simulation example of nonlinear pH neutralization system is discussed to demonstrate the applicability of the proposed algorithm. In the end, we discuss the technology method by VB realization based on MCGS.As is shown in the paper, the intelligent PID controller based on neural network has better control performance and the expansive foreground.