自适应模糊神经网络在炉温控制中的应用  

Adaptive Fuzzy Neural Network Control for Kiln Temperature

作　　者：杜云[1] 吴学礼[2] 孟华[1] 宋哲英[1] 

机构地区：[1]河北科技大学电气信息学院,石家庄050054 [2]华中科技大学控制科学与工程系,武汉430074

出　　处：《仪器仪表学报》2002年第z1期446-448,454,共4页Chinese Journal of Scientific Instrument

基　　金：河北省科技攻关计划资助项目 (0 12 134 0 7D)

摘　　要：针对复杂工业过程系统的特点 ,提出了一种自适应模糊神经网络控制器 ,这种控制器由模糊神经网络控制器 (FNNC)和模型网络 (MNN)组成 ,具有自适应学习能力。着重讨论了自适应模糊神经网络的混合学习算法 ,给出了适于非线形时滞电阻加热炉的控制方案。经仿真和加热炉温控实验表明 。This paper proposes a implement method of adaptive fuzzy neural controllers used in complex industrial processes.This control system consists of a fuzzy neural controller(FNNC) and modeling neural networks(MNN),and has the ability of adaptive learning.A hybrid algorithm for the training of the adaptive neurofuzzy network was discussed.A control scheme based on the adaptive neurofuzzy controller applied to a resistance heating furnace was presented.The effectiveness of the proposed scheme is illustrated through simulation and complex industrial heater temperature control system.

关 键 词：自适应 模糊控制 神经网络 

分 类 号：TP2[自动化与计算机技术—检测技术与自动化装置]