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神经网络优化的迭代学习控制在黄酒发酵中的应用
引用本文:高冬垒,熊伟丽,胡小明,徐保国.神经网络优化的迭代学习控制在黄酒发酵中的应用[J].计算机与应用化学,2012,29(3):305-308.
作者姓名:高冬垒  熊伟丽  胡小明  徐保国
作者单位:1. 江南大学,轻工过程先进控制教育部重点实验室,江苏,无锡,214122
2. 绍兴女儿红酿酒有限公司,浙江,上虞,312352
3. 江南大学物联网工程学院自动化系,江苏,无锡,214122
基金项目:国家自然科学基金项目,中央高校基本科研业务费专项资金资助,江苏省博士后基金项目
摘    要:黄酒发酵过程是一种一边糖化一边发酵的复式发酵方式,在糖化和发酵之间需要建立动态平衡。鉴于发酵温度对活化酶和酵母的影响,本文通过控制反应温度来控制黄酒产品质量。黄酒发酵过程是一个典型的间歇过程,本文运用迭代学习控制对发酵温度进行控制,并利用神经网络优化迭代学习律的增益。仿真结果表明了该方法的有效性,且能在较少的迭代次数下,以最快的收敛速度,较高的跟踪精度逼近期望轨迹。

关 键 词:黄酒发酵  温度控制  迭代学习控制  神经网络

The application of ILC based neural network optimization to rice wine fermentation
Gao Donglei , Xiong Weili , Hu Xiaoming , Xu Baoguo.The application of ILC based neural network optimization to rice wine fermentation[J].Computers and Applied Chemistry,2012,29(3):305-308.
Authors:Gao Donglei  Xiong Weili  Hu Xiaoming  Xu Baoguo
Affiliation:1.Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education),Jiangnan University,Wuxi,214122, Jiangsu,China) (2.Shaoxing Nuerhong Brewing Co.LTD,Shangyu,312352,Zhejiang,China) (3.School of IoT Engineering,Dept.of Automation,Jiangnan University,Wuxi,214122,Jiangsun,China)
Abstract:The fermentation of rice wine is a sort of multi-zymdysis embracing saccharification and fermentation;the two processes need a dynamic balance.The method of ensuring quality of rice wine which controlling the fermentation temperature is used in this paper,since the temperature impacts on both activating enzyme and yeast.A new iterative learning control(ILC)algorithms based on neural network optimization is proposed,as the fermentation is a typical batch process.It advanced that BP neural network optimizes and calculates the parameters of the iterative learning controller,and is suitable to be used on temperature control in the process.The simulation result indicates that the algorithm is much effective and can approach anticipant contrail with less iterative,double-quick convergence and lofty tracking precision.
Keywords:rice wine fermentation  temperature control  iterative learning control  neural network
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