Abstract: Conditioning temperature is one of the key factors in the quality of feed pellets during feed processing. It is a high demand to maintain the constant conditioning temperature. Specifically, too high conditioning temperature can lead to the inactivation of heat-sensitive ingredients, such as probiotics, whereas, too low conditioning temperature can be found in the incomplete sterilization of the starch paste. In this study, a Proportion Integration Differentiation (PID)-based control system was developed to control the conditioning temperature of the feed pellets during processing. The whole unit consisted of a control system, steam piping, and a pelletizer. The control system with a Programmable Logic Controller (PLC) and a touch screen was utilized to control the start/stop of the pelletizer and the opening of the electric regulating valve. The process parameters of the pelletizer were also automatically collected, according to the given time interval. A temperature sensor was installed at the outlet of the pelletizer. The PT100 temperature sensor was used to collect the conditioning temperature of the material at the outlet of the temperature in real time. Subsequently, the collected data was fed back to the PLC. The PID closed-loop control algorithm was utilized to calculate the electric actuator again after the appropriate adjustment of the parameters. The stable control of tempering temperature was realized to change the steam flow into the temperature. A systematic analysis was made to obtain the convective heat exchange process between the mixed feed and steam at temperature. A theoretical model of heat transfer was established to obtain the specific parameters using the step response curve method. After that, the data curve was processed (R2 = 0.976) to obtain a control model between the electric proportional control valve and the tempering temperature in the control system. As such, a large influence of special points was avoided on the experimental data after processing. Furthermore, the simulation analysis was carried out to determine the optimum parameters for the PID control using the Simulink platform. A comparison was performed on the response curves from three PID parameter regulations, namely the Z-N regulation, the decay curve method, and the critical proportional method. Finally, the critical proportional method was found to present the best control effect, in terms of the overshoot and regulation time in the dynamic performance indicators with the PID parameters (proportionality coefficient Kp=52.7, integral coefficient Ti=6.4, and differential coefficient Td= 1.6). The response time of the PID controller obtained by the critical proportionality method was 14 s and the overshoot was 3.3 ℃. Taking the lactating sow meal as an example, a series of prototype tests were carried out on the pelletizer. Specifically, the lactating sow meal was first crushed with the 1.5 and 2 mm sieves. The moisture content of the mixture was 10.17%, while the tempering temperature was set at 75, 80, and 85 °C. The tempering temperature was maintained within the set range after stability. Subsequently, the tempering temperature of 80 °C was chosen for the stability test. The tempering temperature was recorded every 1min during the test. The basically stable tempering temperature was achieved in the whole test process, which was controlled within (80±1) ℃, indicating the small average relative error and coefficient of variation of temperature. Therefore, the stable control of system temperature can be expected to automatically collect the pelletizing production data. Anyway, the control system can be expected to serve as the rapid response and real-time control of tempering temperature in the pelletizing process. Furthermore, the processing operation was simplified to improve automation in pelletizing production.