一种基于模糊神经网络FNN在加热炉温度控制中的应用  

The Application of Temperature Control of Heating Furnace Based on Fuzzy Neural Networks

作　　者：刘会景[1] 刘节影[2] 

机构地区：[1]昆明理工大学,昆明650233 [2]中国矿业大学(北京)资源学院,北京100083

出　　处：《冶金设备》2007年第4期11-14,共4页Metallurgical Equipment

基　　金：云南省教育厅科学研究基金项目;项目编号为042140D

摘　　要：从实际出发,以昆明钢铁集团公司中板厂加热炉为研究对象,对具有时变性、非线性、模糊性的随机过程进行了研究。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,采用了一种新型的智能控制方案——模糊神经网络控制。对提出的模糊神经网络控制算法进行了仿真试验,仿真结果表明,对比PID控制和自整定PID控制,采用本文所提出的模糊神经网络控制算法对加热炉进行控制,具有推理速度快,跟踪性能好,抗干扰能力强的优点,它完全能够满足工业生产需要,具有较强的可行性和实用性。In view of practical use, taking the furnace of the medium-plate plant of Kunming Iron ＆ Steel Company as object, the thesis studies the casual process of time variable, nonlinear and indefinite. The feasibility and the form of combining neural network and fuzzy system are discussed. The new theory of Fuzzy Neural Networks Control （ F NNC）, which combines the neural networks with the fuzzy logic, is put forward in this paper. The simu- lation experiments are made for the arithmetic of fuzzy neural networks control. Comparisons are made among the arithmetic, PID control and fuzzy self-tuning PID control. It is showed that satisfied performance, strong robustness and disturbance-rejection are obtained by using the arithmetic put forward in this thesis.

关 键 词：加热炉 模糊控制 神经网络 PID控制 

分 类 号：TG307[金属学及工艺—金属压力加工]