The work aims to design a temperature controller, in order to improve the temperature control precision of the preheating system of aseptic brick bale equipment. A temperature controller was designed based on the fuzzy neural network algorithm. On the basis of hardware structure of the preheating system, the mathematical model of the controlled object was established. Taking advantage of the good convergence of fuzzy control and the operation advantage of fuzzy quantity, as well as the self-learning and self-adaptive characteristics of neural network, a PID control strategy based on fuzzy neural network was proposed by combining the conventional PID control with fuzzy control and neural network, so as to realize the real-time online tuning of PID parameters. Experimental results showed that, compared with other methods, the proposed control method could reduce the temperature overshoot from 2.6 ℃ to 0.9 ℃, and the steady-state deviation from ±1 ℃ to ±0.4 ℃. The proposed method can meet the requirement of preheating system temperature control.