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模糊神经网络在解耦控制中的研究
引用本文:平玉环,李宗耀,孙剑. 模糊神经网络在解耦控制中的研究[J]. 控制工程, 2009, 16(4)
作者姓名:平玉环  李宗耀  孙剑
作者单位:华北电力大学,科技学院,河北,保定,071003;定洲电厂,设备部,河北,定州,071003
基金项目:华北电力大学博士基金 
摘    要:在工业生产过程中,针时纯迟延、时变、强耦合的多输入多输出现象,提出一种基于模糊神经网络解耦和PID控制相结合,对系统进行解耦控制的方法.这种方法不需要建立多变量对象精确的数学模型,通过对大迟延大惯性强耦合的循环流化床锅炉床温-主汽压力对象进行仿真,其结果表明,解耦控制效果很好,具有良好的静态性、动态性及鲁棒性.

关 键 词:耦舍对象  模糊神经网络  解耦控制  仿真试验

Application of Fuzzy Neural Network to Decoupling Control
PING Yu-huan,LI Zong-yao,SUN Jian. Application of Fuzzy Neural Network to Decoupling Control[J]. Control Engineering of China, 2009, 16(4)
Authors:PING Yu-huan  LI Zong-yao  SUN Jian
Affiliation:1.Technical Institute;North China Electric Power University;Baoding 071003;China;2.Equipment Department;Dingzhou Power Plant;Dingzhou 071003;China
Abstract:In the industrial production process,to the problems of the pure delay,time-variation and the strong coupling of the multi-input and multi-output phenomenon,a method is proposed that does not need to establish the precise multiple variable object mathematical model,based on the union of the fuzzy neural network decoupling and the PID control to control the decoupling of the system.The simulation result to the double-input and double-output coupling objects shows that this method has a good decoupling contro...
Keywords:coupling object  fuzzy neural network  decoupling control  simulation experimen
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