In response to issues of poor control accuracy and insufficient stability in pulverized coal burner control systems caused by nonlinear factors, this paper proposed a fuzzy PID control strategy deeply optimized based on genetic algorithms (GA), leveraging GA’s unique global convergence and parallel optimization capabilities. The parameters of the fuzzy PID controller were optimized using a genetic algorithm, enabling rapid tuning of the system’s weight factors, thus significantly enhancing its control performance and achieving precise control of burner temperature. MATLAB was used for simulation experiments, with comparative analysis against conventional PID and fuzzy PID control methods. The study shows that system optimization of fuzzy PID through genetic algorithms can effectively reduce errors and improve the control effect of the burner temperature control system. The optimized fuzzy PID controller demonstrates faster response speed, smaller overshoot, and a shorter time to reach steady state compared to conventional PID and fuzzy PID.