基于标准粒子群算法对热工模型的辨识

Thermal Model Identification Based on the Standard Particle Swarm Optimization Algorithm

针对热工系统建模中的模型辨识问题,采用标准粒子群算法去辨识热工系统的模型;介绍了粒子群算法和标准粒子群算法的基本思想,以及利用标准粒子群算法进行系统辨识的基本原理与计算方法,并且利用Matlab数学工具对该方法在火电厂生产过程中蒸汽变化量对汽包水位的影响的传递函数,以及送风量和引风量变化对炉膛负压影响的传递函数的系统辨识进行了仿真研究,得到了这两个系统的数学模型,仿真结果显示所得的这两个数学模型与实际的现场数据有一定的吻合性,对火电厂热工系统的研究以及运行操作人员具有一定的指导意义。

For the problem of model identification in the study of modeling of the thermal system, the standard particle swarm optimization （PSO） algorithm is used to identify thermal system models. The basic ideas of PSO, and standard PSO, as well as the basic principle and calculation methods of system identification in standard PSO algorithm are introduced. A research on the identification of the transfer function which includes influence of steam variation to the steam drum water level and changes of air volume and input to the negative pressure of furnace during the process of power production is carried out using the Matlab mathematical tool. Finally, two mathematical models of these two kinds of processes are acquired. As shown in the simulating results, these two kinds of mathe- matical model ultimately identified have a certain similarity compared with the actual field data, which has a certain guiding significance to the operating people and the study of thermal system in the power plants.