Steam-gas pressurizer is used in small modular reactors (SMRs) because of its simple structure and the absence of heating and spraying systems. It is very important to study the control scheme of steam-gas pressurizer for reactor system design. In this paper, the SMR primary loop model and the steam-gas pressurizer system model are established by a one-dimensional simulation program. The design of BP Neural Network PID controller is implemented by PYTHON programming language. One-dimensional simulation program and PYTHON programming language are coupled to simulate and compare the dynamic control of steam-gas pressurizer under different controller methods. The results show that under different transient conditions, the parameters of BP Neural Network PID controller can be dynamically adjusted, which has better control effect on meeting the control requirements of reactor safe operation. The pressure overshoot of the steam-gas pressurizer is smaller and the stability time is shorter based on BP Neural Network PID controller, and it has obvious advantages over the traditional PID method. The relevant conclusions in this paper provide a reference for the design of the pressurizer system for SMRs.