A Study of Optimization Strategy for Furnace Temperature Control System Based on Particle Swarm Optimization (PSO)

The stability of furnace temperature holds significant importance in modern industry, as it directly impacts the product quality, production efficiency, and energy utilization efficiency during industrial processes. With the continuous development of modern industry, the demand for improved furnace temperature stability has escalated, indicating the need for a more advanced furnace temperature control system. In this paper, firstly modeling of a traditional furnace temperature control system was conducted and pertinent parameter analysis was carried out. Secondly, Particle Swarm Optimization (PSO) was introduced to optimize the control system, proposing an optimized control strategy based on PSO. Finally, Matlab was used to solve the system parameters based on PSO, and Simulink was used to verify the performance of the optimized system. The study concluded that the optimization research on the furnace temperature control system led to substantial improvements in system performance, specifically increasing the cutoff frequency from the original 0.274 rad/s to a significantly higher value of 8.61 rad/s and enhancing the stability margin from 41.2° to 50.74°. These enhancements effectively improve the responsiveness and stability of the system. The feasibility and effectiveness of the optimization design method have been successfully validated through simulation, providing an effective basis for the subsequent design of furnace temperature control system.