Soft Sensor Modeling of the Penicillin Fermentation Based on FCM Clustering and LS-SVM

摘要：

In dealing with the problem that the important parameters of a penicillin fermentation process are hard to measure precisely, such as biomass concentration and production concentration, therefore, a soft sensor modeling for the penicillin fermentation based on fuzzy c-means clustering and least square support vector machine (LS-SVM) is proposed. First of all, features of sample data are extracted and the secondary variables are determined by principal component analysis (PCA). And then, in order to predict these important biological parameters, a fuzzy c-means clustering (FCM) algorithm is applied to group the training data into several clusters, and LS-SVM is used to construct models based on each cluster. The simulation example shows that the method could measure the important parameters which could not be measured online during the course of the penicillin fermentation with a high precision.

关键词： PCA fuzzy c-means clustering penicillin fermentation LS-SVM soft-senor

作者: Yu.Kirn.Sun Yong.He Xiao.Fu.Ji

作者单位: College of Electronic and Information Engineering Jiangsu University Zhenjiang,Jiangsu,China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 12-16

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）