自适应模糊神经网络控制器在电阻加热炉中的应用  

Adaptive Neurofuzzy Controller Applied to Resistance Heating Furnaces

作　　者：李歧强[1] 钱积新[1] 李现明[2] 金萍[2] 

机构地区：[1]浙江大学工业控制技术国家重点实验室 [2]山东工业大学

出　　处：《控制与决策》1999年第2期189-192,共4页Control and Decision

摘　　要：提出一种自适应模糊神经网络控制器，着重讨论了自适应模糊神经网络的混合学习算法和自适应动量解耦的最速下降法。给出了适于非线性时滞、基于径向基函数网络和自适应模糊神经网络控制器的控制方案，并把它用在电阻加热炉中。实际应用表明，模糊神经网络控制器具有良好的控制效果。An adaptive neurofuzzy controller was proposed. A hybrid algorithm and an adaptive decoupled momentum based steepest descent algorithm for the training of the adaptive neurofuzzy network were discussed. A control scheme based on RBF networks and the adaptive neurofuzzy controller was presented and applied to a resistance heating furnace. Practical application demonstrates that the adaptive neurofuzzy controller has very good performances.

关 键 词：模糊神经网络 电阻加热炉 自适应控制器 

分 类 号：TM924.2[电气工程—电力电子与电力传动] TM571