Abstract: According to the influence of stopper and drawing speed on the online control of continuous casting crystallizer liquid level, an optimization algorithm combining BP neural network and fuzzy PID was proposed. According to the continuous casting crystallizer liquid level control model, BP neural network was used to quantify the influencing factors of the molten metal inflow to the position of the stopper, and then fuzzy PID was used to correlate the liquid level in the crystallizer with the correction amount of the stopper position and the drawing speed.PID parameters can be adjusted online to achieve optimal control of the liquid level in the crystallizer.The simulation results show that the BP neural network and fuzzy PID can avoid the overshoot of the continuous casting mold level control, make the level fluctuation stabilize in a short time, reduce the control deviation of the liquid level and reduce the influence of uncertain disturbances such as stopper and drawing speed on the quality of the cast billet.