Streptomycin fermentation process modeling with principal componentanalysis and fuzzy model
Nat. Key Lab. of Ind. Control Technol., Zhejiang Univ., HangzhouDOI: 10.1109/WCICA.2000.862969 Conference: Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on, Volume: 3
Source: IEEE Xplore
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
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.