Simulation Analysis of Temperature Controlling for Resistance Furnace Based on Hybrid Particle Swarm Optimization

The temperature is an important parameter for resistance furnace among the industries. Its nonlinear characteristics makes it is difficult to be controlled, therefore it is necessary to find out an effective method to get the resistance furnace temperature under control. The hybrid particle swarm algorithm and PID controller are combined to design the temperature controlling system of resistance furnace. Based on real situation of resistance furnace temperature control, the mathematical model of hybrid particle swarm algorithm is established. The chemotaxis, dispersion and reproduction of bacteria are introduced into the hybrid particle warm algorithm. According to the controlling theory, the basic procedure of hybrid PSO algorithm is designed and a temperature control system used for resistance furnace is developed too. The performance of control system is tested through simulation analysis and the simulation results are compared with the onsite data collected. The results of simulation show that the simulation value is close to the measured value, therefore, good resistance furnace temperature control result is obtained.