基于神经网络的模糊控制在炼钢加热炉温度控制中的应用  

Application of Fuzzy PID Control Based on BP Neural Network on Flux Control of Coal Gas for Furnace

作　　者：刘会景[1] 李琨[1] 刘节影[1] 

机构地区：[1]昆明理工大学信息工程与自动化学院,云南昆明650051

出　　处：《湿法冶金》2008年第2期120-123,共4页Hydrometallurgy of China

基　　金：云南省教育厅科学研究基金项目[基于DSP的信息整合技术的研究与开发](编号042140D)

摘　　要：钢厂加热炉是一个复杂的受控对象,存在着非线性、时变性、纯滞后因素和不确定随机干扰等因素。从对其燃烧状况的分析来看,加热炉温度的调节主要是靠对煤气流量的控制来完成的,因而确立一种合理的煤气流量控制方案是实现加热炉燃烧智能化控制的关键。提出了将模糊控制、PID控制和神经网络3种技术相结合,共同控制煤气流量。仿真研究结果表明,这种BP神经网络模糊PID控制在克服对象的大惯性、抗干扰性、非线性和纯滞后方面,大大改善了控制品质。The furnace of steel company is a complex object controlled and has the casual properties of nonlinear, time-variability and pure lag and casual disturbance. Considering burning conditions, temperature adjusting of the furnace is accomplished mainly by controling coal gas flux. Therefore, coal gas flux control is the key of realizing the intelligent control burning of the furnace. Associating BP neural network and fuzzy system with PID control to control coal gas flux of the furnace is introduced. The simulation research results shows that the big inertia time-variability, pure lag and random disturbance of the furnace can be overcome, and control quality considerably is improved.

关 键 词：BP神经网络 模糊控制 PID 流量控制 

分 类 号：TP273.4[自动化与计算机技术—检测技术与自动化装置] TP183[自动化与计算机技术—控制科学与工程]