基于FNN在蒸馏装置常压加热炉上的应用  

Using FNN on Distillation Device of Ordinary Pressure Mill Furnace

作　　者：王建平[1] 加玛力汗.库马什 李涛[1] 

机构地区：[1]新疆大学电气工程学院,新疆乌鲁木齐830008

出　　处：《计算机测量与控制》2010年第11期2649-2651,共3页Computer Measurement &Control

摘　　要：蒸馏装置的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;着重研究了神经网络与模糊系统融合的可行性及融合方式,提出了将模糊控制和神经网络两种技术相结合,共同控制;仿真研究结果表明,这种神经网络模糊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;最后进行了现场实验,实验表明,所应用的控制器性能令人满意,具有很好的鲁棒性,一定会具有更广阔的发展前景。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.studies the neural network and fuzzy system,the feasibility of the integration and fusion.Associating neural network and fuzzy system 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.Finally,the experimental results show that the performance of controller is satisfactory,and it has the very good robustness,and will have more broad development prospects.

关 键 词：加热炉 模糊控制 神经网络 抗干扰 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]