Streptomycin fermentation process modeling with principal component analysis and fuzzy model

Analysis, modeling and control for a fed-batch fermentation process still remain challenging issues. Based on principal component analysis (PCA) and fuzzy modelling a simple and efficient approach to monitoring fed-batch streptomycin fermentation is presented. The data obtained from an industrial streptomycin fermentation process is first analyzed with PCA so that the large multivariate data with highly correlated and noisy measurements can be compressed into a lower dimension space which contains most of the variance of the original matrix. Moreover, a fuzzy model is used to construct a product (antibiotic) concentration estimator of the streptomycin fermentation process, prior knowledge and expertise are important in fed-batch fermentation processes. The results of the fuzzy model compared with a linear multivariate regression model indicate the potential of the fuzzy model as a state estimator of all such industrial fed-batch processes.