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基于逆系统的赖氨酸发酵多变量解耦内模控制
引用本文:孙晓天,靳其兵,张瑶,徐海涛.基于逆系统的赖氨酸发酵多变量解耦内模控制[J].电子技术应用,2010,36(2).
作者姓名:孙晓天  靳其兵  张瑶  徐海涛
作者单位:1. 北京化工大学信息科学与技术学院,北京,100029
2. 江苏大学电气信息工程学院,江苏,镇江,212013
基金项目:国家高技术研究发展计划(863计划),国家重点基础研究发展规划(973计划) 
摘    要:针对赖氨酸发酵过程的时变、非线性和高耦合性,提出基于逆系统的赖氨酸发酵多变量解耦内模控制方法。根据动态递归模糊神经网络(DRFNN)的非线性辨识原理离线建立发酵过程的逆模型,将得到的逆模型串联在发酵系统之前,实现了发酵过程输入输出解耦线性化,从而得到伪线性系统;对复合后的伪线性系统采用内模控制。仿真结果表明,该方法能够适应赖氨酸发酵过程模型的不确定性和参数的时变性,具有较强的鲁棒性,且结构简单,易于实现。

关 键 词:基于动态递归模糊神经网络(DRFNN)  逆系统  赖氨酸  解耦  内模控制

Multivariable internal model decoupling control based on inverse system in lysine fermentation process
SUN Xiao Tian,JIN Qi Bing,ZHANG Yao,XU Hai Tao.Multivariable internal model decoupling control based on inverse system in lysine fermentation process[J].Application of Electronic Technique,2010,36(2).
Authors:SUN Xiao Tian  JIN Qi Bing  ZHANG Yao  XU Hai Tao
Affiliation:SUN Xiao Tian1,JIN Qi Bing1,ZHANG Yao2,XU Hai Tao1(1.College of Information Science and Technology,Beijing University of Chemical Technology,Beijing 100029 China,2.School of Electrical and Information Engineering,Jiangsu University,Zhenjiang 212013,China)
Abstract:In view of lysine fermentative process time-variable,nonlinear and high coupling,multivariable internal model decoupling control based on inverse system in lysine fermentation process is proposed.First,according to the nonlinear identification theory of dynamic recursive fuzzy neural network(DRFNN),the nonlinear inverse model of the plant was built offline,the dynamic recursive fuzzy neural network(DRFNN) inverse model was cascaded before the fermentation system to be linear pseudo-linear system based on in...
Keywords:dynamic recursive fuzzy neural network(DRFNN)  inverse system  lysine  decoupling  internal model control  
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