摘要
基于主元分析和模糊模型 ,提出了一种简单而有效的链霉素发酵过程产物浓度的预报方法 .该方法采用主元分析压缩关联程度高且含有测量噪声的实际工业生产数据 ,筛选出影响产物浓度的主要过程变量 ,构造了模糊分段线性模型的产物浓度估计器 .与线性多元回归模型相比 ,模糊模型更适合作为间歇发酵过程的状态估计器 .
Analysis, modeling and control for fed batch fermentation process still remain a challenging issue. Based on Principal Component Analysis(PCA) and fuzzy model, a simple and efficient approach to monitor the fed batch streptomycin fermentation is presented. The data obtained from industrial streptomycin fermentation process were preliminary analyzed with PCA so that the large multivariate data with highly correlated and noisy measuremnts can be compressed into a lower dimension space which contains most of the variance of the original matrix. Moreover, fuzzy model was used to construct a product (antibiotic) concentration estimator of the streptomycin fermentation process in that prior knowledge and expertise are important in fed batch fermentation processes. The results of fuzzy model comparing with linear multivariate regression model indicate that the potential of fuzzy model as state estimator of all such industrial fed batch processes.
关键词
链霉素发酵
主元分析
模糊模型
监控
浓度估计器
streptomycin fermentation
principal component analysis
fuzzy model
monitoring