基于模糊神经网络α阶逆系统的发酵过程多变量解耦控制(英文)  

Multivariable decoupling control based on fuzzy-neural network αth-order inverse system in fermentation process

作　　者：孙玉坤[1] 王博[1] 嵇小辅[1] 黄永红[1] 

机构地区：[1]江苏大学电气信息工程学院,江苏镇江212013

出　　处：《控制理论与应用》2010年第2期188-192,共5页Control Theory & Applications

基　　金：supported by the National High-Tech Research and Development Program under grant 2007AA04Z179;the Research Found for the Doctoral Program of Higher Education of China under grant 20070299010;the Professional Research Foundation for Advanced Talents of Jiangsu University under grant 07JDG037;the Open Project of the National Key Laboratory of Industrial Control Technology in Zhejiang University under grant ICT0910

摘　　要：将逆系统方法与模糊神经网络相结合,提出一种基于模糊神经网络α阶逆系统的发酵过程解耦控制方法.在分析了系统可逆性的基础上,利用模糊神经网络建立发酵过程的非线性逆模型,然后将得到的模糊神经α阶逆系统与发酵过程串联复合成伪线性系统,最后设计专家控制器实现高性能闭环解耦控制.仿真结果表明,提出的解耦控制方法能够适应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,克服了解析逆系统解耦控制方法依赖于过程模型和对模型参数的变化很敏感的缺点,且结构简单,易于实现.This paper proposes a nonlinear multivariable decoupling control strategy based on fuzzy-neural networkαth-order inverse method that combines inverse system theory with fuzzy-neural network for fermentation process. A nonlinear inverse model is developed based on the reversibility analysis of the process model. A fuzzy-neural network αth-order inverse system is then constructed, which is cascaded with this process to transform the original nonlinear system to a pseudo-linear system. Finally, an expert controller is used to closed-loop synthesis. The effectiveness of the presented method is illustrated by a simulation experiment.

关 键 词：生化反应过程 模糊神经网络 逆系统方法 解耦控制 专家控制器 

分 类 号：TQ920.1[轻工技术与工程—发酵工程] TP183[自动化与计算机技术—控制理论与控制工程]