基于改进蚁群算法的参数寻优在过热汽温控制中的应用  

Application of Parameter Optimization Based on Improved Ant Colony Algorithm in Superheated Steam Temperature Control

作　　者：李思莹 Li Siying

机构地区：[1]滁州学院计算机与信息工程学院,安徽滁州239000

出　　处：《滁州学院学报》2022年第2期13-19,共7页Journal of Chuzhou University

基　　金：滁州学院校级科研启动基金资助项目“面向光伏行业的智能物联网与应用技术研究”(2022qd040)。

摘　　要：文章提出了一种基于改进蚁群算法的参数寻优方法。首先,针对蚁群算法搜索最优解的范围存在局限、容易陷入局部最优的问题,将莱维飞行的思想运用到信息素蒸发系数的寻优中,扩大了最优解的搜索范围,避免了陷入局部最优的局限性。其次,为了改善火电厂过热汽温系统的控制品质,将提出的改进蚁群算法运用到火电厂过热汽温系统的参数寻优中,先后完成了过热汽温系统的模型辨识和主副回路控制器的参数优化。最后,为了验证提出方法的有效性,采用国内某600MW火电厂机组的历史运行数据进行仿真试验,试验结果证明了该方法的可行性和有效性。A parameter optimization method based on improved ant colony algorithm is proposed.First of all,in view of the limited range of ant colony algorithm to search for the optimal solution,and it is easy to fall into the local optimal problem,this paper applies the idea of Levi's flight to the optimization of pheromone evaporation coefficient,and expands the search range of the optimal solution.Avoid the limitations of falling into local optima.Secondly,in order to improve the control quality of the superheated steam temperature system of the thermal power plant,the improved ant colony algorithm proposed in this paper is applied to the parameter optimization of the superheated steam temperature system of the thermal power plant,and the model identification of the superheated steam temperature system and the main and secondary loops have been completed successively.Parameter optimization of the controller.Finally,in order to verify the effectiveness of the method proposed in this paper,the historical operation data of a 600MW thermal power plant in China is used to conduct a simulation test.The test results prove the feasibility and effectiveness of the method.

关 键 词：蚁群算法 莱维飞行 过热汽温控制 参数寻优 

分 类 号：TM28[一般工业技术—材料科学与工程]