The temperature control system of reheating furnace has the defects of nonlinearity, timevarying and hysteresis, which results in slow response speed and poor antiinterference ability in the process of system control. The traditional control method cannot control it accurately. The immune algorithm was introduced into the ant colony algorithm. According to the affinity principle of the immune algorithm, the diversity of the ant colony was increased, and the initial pheromone rule of the ant colony was improved. The improved ant colony algorithm was used to adjust the weight of PID neural network (PIDNN), and a new PIDNN control method was proposed. The simulation results show that, compared with the traditional PIDNN control method, when the PIDNN controller based on the improved ant colony algorithm was used to control the heating furnace, the time required for the system to reach the steady state was reduced by about 34%; when the disturbance was added, the time required for the system to return to the steady state was reduced by about 26%, the vibration amplitude was significantly reduced, and the antiinterference ability of the heating furnace control system was enhanced.