Neural Network PID Control of Water Level in Nuclear Power Plant Regulator

The water level control system of the nuclear power plant regulator is a complex system with time-varying and delayed characteristics. If only traditional PID (Proportional Integral Derivative) controllers are used, the control effect is not ideal, and there may be a series of problems such as significant overshoot and difficulty in stability. In order to eliminate these defects, this article introduces neural networks into PID controllers. Firstly, the structural mode and basic principles of the neural network were explained in detail. Then, MATLAB software was used to simulate and design the controller and its improved form in Simulink. Finally, the control effects before and after the improvement were compared, and it can be seen that the neural network PID control can effectively eliminate overshoot, shorten transition time and rise time.