Abstract:

In the research on the thermal efficiency of atmospheric tube heating furnaces, it is necessary to conduct effective online measurement of thermal efficiency and select relatively reliable advanced control methods. On the basis of the research on the combustion mechanism of the heating furnace, the online measurement method based on the principle and data processing is used to process the thermal efficiency, and the "dynamic matrix control" is introduced in the process of optimizing the control of the heating furnace efficiency, which is compared with the traditional control method. The introduction of dynamic matrix control makes the system have a better control effect. At the same time, the "particle swarm algorithm" was selected to optimize the parameters of dynamic matrix control. In the optimization process of dynamic matrix parameters, the particle swarm algorithm relatively shortens the optimization time and improves the control quality, so as to achieve a more satisfactory control effect. Finally, compare with internal model control, it shows that dynamic matrix control can achieve relatively better control effect.

Key words: Heating furnace, Thermal efficiency, Dynamic matrix control(DMC), Particle swarm optimization(PSO)

摘要：

在常压管式加热炉热效率的研究中，需要对热效率进行有效的在线测量并且选用相对可靠的先进控制方法。在研究加热炉燃烧机理的基础上，采用基于原理和数据处理的在线测量方法，并在加热炉效率优化控制的过程中引入了动态矩阵控制方法。与传统的控制方法相比，动态矩阵控制的引入使系统具有更好的控制效果。同时，选择粒子群算法对动态矩阵控制的参数进行了寻优处理。粒子群算法在动态矩阵参数的寻优过程中相对缩短了寻优时间，并提升了控制品质。最后，与内模控制进行了比较。结果表明，动态矩阵控制方法可以达到更好的控制效果。

关键词: 加热炉, 热效率, 动态矩阵控制, 粒子群优化算法