Design of circulating temperature control system for rubber and plastic industry based on mechatronics

Introduction In the modern rubber and plastics industry, temperature control becomes a key factor affecting product quality and production efficiency. However, the existing temperature control system generally has the problem of temperature lag and high energy consumption. Aiming at the problem of poor control effect of current temperature control system, a new circulating temperature control system for plastic industry was proposed in this study. Methods Firstly, fuzzy neural network and improved particle swarm optimization algorithm were introduced in this study, and then the hybrid algorithm was combined with mechatronics technology to design and implement a set of rubber and plastic industry cycle temperature control system. Results According to the test data, the improved algorithm performed well in both scenarios. Compared with the comparison algorithm, the improved algorithm has the following parameters: tuning time (scenario 1:513s, scenario 2:521s), overshoot (scenario 1:2.5%, scenario 2:2.3%), steady-state error (scenario 1:005, scenario 2:004) and absolute integral error (scenario 1:008, scenario 2: 0.007) has been significantly optimized. Simulation analysis shows that the proposed temperature control system has stronger anti-interference ability and lower energy consumption (0.6 hour energy consumption: 1086.5J, energy saving rate: 38.7%). Discussion The results show that the cyclic temperature control system of rubber and plastics industry is superior to the comparison system in terms of temperature control performance, anti-interference ability and energy consumption. The research not only improves the accuracy and efficiency of temperature control systems in the rubber and plastics industry, but also promotes the promotion of green and sustainable production methods. This is essential to promote the high-quality development of the plastics and rubber industry.