To address the problem that dynamic temperature stability is difficult to ensure due to factors such as nonlinearity, time-varying properties, and external disturbances in the extruder temperature control process, this paper proposes a dynamic temperature stability control method for the extruder based on an intelligent fuzzy algorithm (IFA). First, a mathematical model is established for the thermal inertia and hysteresis characteristics of the extruder heating system. Combining fuzzy control theory with an adaptive adjustment mechanism, an intelligent controller is designed with fuzzy reasoning as the core and parameter self-adjustment as the supplement. The specific steps include: 1) modeling the temperature acquisition and PID basic control loop of the extruder heating zone; 2) introducing a fuzzy control rule library to dynamically adjust the PID parameters based on experience and data; 3) using an adaptive algorithm to correct the fuzzy membership function in real time to improve the system’s robustness to disturbances; and 4) comparing and analyzing the control effects through a simulation platform and actual extrusion experiments. The results show that the temperature fluctuation amplitude of the proposed method under load disturbance is reduced from ±4.8℃ of traditional PID control to ±0.7℃, which verifies the superiority of the method in temperature dynamic stability. The temperature control method based on intelligent fuzzy algorithm effectively improves the automation of the extruder and the stability of product quality.
Pan et al. (Thu,) studied this question.