I. Introduction The production of high-performance plastic products requires not only the correct use of raw materials, but also the crucial selection of processing equipment and process parameters. Precise temperature control of each section of the extruder barrel and die head is essential for improving the stability of extruder output and ensuring performance. Currently, most economical plastic extruders in China commonly employ either a separate instrument control scheme or a PLC centralized control scheme for their temperature control systems. While the separate instrument control scheme offers the advantage of low price, it suffers from several limitations in control functionality. Specifically, it requires individual control of each separate unit, preventing comprehensive system control. The use of multiple temperature controllers complicates the temperature control circuit structure, increases the failure rate, and, because most temperature controllers operate on an intermittent control method, causes significant temperature fluctuations in each heating zone, affecting the processing quality of plastic products. The PLC centralized control scheme, while enabling comprehensive system control, requires complex multi-loop PID temperature control algorithms, consumes significant CPU resources, and struggles to achieve high-precision temperature control when there are more than eight temperature zones. Using a high-end CPU to build the system results in high costs and low cost-effectiveness. To address the above issues, we adopted a multi-loop PID temperature control intelligent module as the control core to construct the extruder's temperature control system. This temperature control system features simple hardware, high temperature control accuracy, and stable performance, making it highly practical. The system can be matched with various types of low-level PLCs, offering advantages such as high temperature control accuracy, simple hardware, low price, and stable reliability. II. System Configuration and Function Introduction As mentioned above, traditional control methods include separate instrument control and PLC centralized control. The first method lacks the significance of centralized control and will not be analyzed further. The hardware configuration of a centralized control system with 16 temperature zones using a Siemens S7-300 PLC is shown in Figure 1: [align=center] Figure 1. Hardware Configuration of PLC Centralized Temperature Control System[/align] In the figure, SM331 is an eight-channel thermocouple input module, SM322 is a 16-channel switch output module, and CPU314 is a mid-range Siemens CPU, serving as the control core for the multi-loop PID control. Considering the potential heating and cooling needs of each temperature zone, the system is configured with two SM331 and two SM322 microcontrollers, forming a control system with 16 temperature inputs and 32 digital outputs (other digital inputs and outputs are ignored). The control accuracy of this system depends on the processing speed of the CPU314 and the PID algorithm. If the standard PID function block of STEP7 is used, it is difficult to achieve ideal results for controlled objects with pure time delay and large inertia; writing a dedicated PID control algorithm is also quite difficult. This system also suffers from increased price and decreased control accuracy as the number of temperature zones increases (around 30 in many models). Using a multi-loop PID temperature control intelligent module as the core, matched with a low-level PLC to construct a temperature control system for a plastic extruder is an ideal solution for multi-temperature zone control. The system hardware configuration is shown in Figure 2: [align=center] Figure 2. Hardware configuration of the temperature control system with multi-loop PID temperature control module[/align] In the figure, M_PID4R_K is a four-loop PID temperature control intelligent module with independent intellectual property rights developed and produced by Foshan Haoke Control Technology Co., Ltd. Since each loop of the module has independent heating and cooling switch outputs, only 4 modules need to be configured. Each module can independently control the temperature value of the corresponding loop. The CPU can easily control the opening and closing of each loop and obtain the current temperature and set temperature value of each loop through the fieldbus. Therefore, the CPU can be Siemens' low-end S7-200 CPU-226, which greatly simplifies the system hardware and software, significantly reduces the system price (only one-third of the original system price), and greatly improves the system's control accuracy, reliability, and stability. The four-loop PID temperature control intelligent module has excellent electrical performance, including a 24VDC input interface with 1500V electrical isolation, four independently isolated thermocouple inputs, four sets of independently isolated transistor or relay switch outputs, and an RS485 isolated communication port supporting MODBUS/RTU protocol. By connecting to a host computer supporting the MODBUS fieldbus protocol, up to 128 slave devices can be added, enabling control of 512 temperature zones. It's worth noting that the PID algorithm of this control module is a fuzzy adaptive PID control algorithm developed for objects with pure time delay and large inertia, making it ideal for precise multi-temperature zone control in machinery such as plastic screw extruders, thermoforming machines, and injection molding machines. III. Working Principle of the Four-Loop PID Temperature Control Intelligent Module The four-loop PID temperature control intelligent module can be viewed as four independent closed-loop feedback control systems. Within one sampling cycle, the temperature sensor (thermocouple) compares the detected barrel and die head temperature signal PV with the setpoint SV to obtain the deviation e = SV - PV. Combining the given P, I, and D parameters and temperature control strategy, PID calculations are performed to obtain the control output value. After pulse width modulation, the conduction time of the relay within one sampling cycle is finally obtained. By controlling the conduction time of the relay within one sampling cycle, the heating time of the heater or the working time of the cooling fan can be controlled, thereby achieving precise temperature control. The four loops operate independently without interference, exhibiting extremely high stability and reliability. IV. Temperature Control Strategy When performing PID control, proportional control reflects the magnitude of the system deviation. As long as a deviation exists, proportional control will generate a control action to reduce the deviation. Derivative control generates a control action based on the changing trend of the deviation, which can improve the dynamic response speed of the system. Integral control generates a control action based on the change of the integral of the deviation, which has a lag effect on the system control and can eliminate static errors. Increasing the integral time constant can improve static accuracy, but if the integral action is too strong, especially when the system deviation is large, it will cause integral saturation, resulting in a large overshoot and even oscillation. The temperature control strategy of the four-loop PID temperature control intelligent module is shown in Figure 3: [align=center] Figure 3 Temperature deviation adopts different temperature control strategies[/align] 1) When the actual temperature is lower than T1, full power heating is used to speed up the response. 2) When the actual temperature is in the range of [T1～T2], PD control is used to avoid integral saturation by separating the integral term. 3) When the actual temperature is in the range of [T2～T3], PID control is used. 4) When the actual temperature is within the range of [T3～T4], fuzzy adaptive PID control is adopted. 5) When the measured temperature is greater than T4, the fan power is turned on for forced cooling. T1, T2, T3, and T4 can be configured to the module through parameter settings, or the module can automatically tune it. This control strategy not only considers the deviation between the measured temperature and the set temperature, but also the trend of the measured temperature change, reducing overshoot and fluctuations, and has a very flexible adaptive effect. The actual temperature curve is shown in Figure 4. [align=center] Figure 4. Measured temperature control curve[/align] V. Conclusion This paper proposes a cost-effective solution for a temperature control system for plastic extruders. This solution not only reduces the system configuration cost, but also greatly improves the system's control accuracy, stability, and scalability. It is very suitable for use in various multi-temperature zone control devices. The results from the use of the plastic extruders from several companies show that under the control of the new temperature control system, the extruders operate smoothly, achieving good control results, with fast temperature control speed, temperature overshoot less than 3℃, and static error less than ±1℃. This controller is not only used in plastic extruders, but also in temperature control of injection molding machines, thermoforming machines, blow molding machines, and other machinery, showing broad application prospects.