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Model‐based control of batch chromatography
Author(s) -
Dünnebier Guido,
Engell Sebastian,
Epping Achim,
Hanisch Felix,
Jupke Andreas,
Klatt KarstenUlrich,
SchmidtTraub Henner
Publication year - 2001
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.690471112
Subject(s) - process engineering , process (computing) , process control , quality (philosophy) , chromatographic separation , chemical industry , control (management) , separation process , computer science , biochemical engineering , chromatography , chemistry , engineering , high performance liquid chromatography , artificial intelligence , epistemology , philosophy , organic chemistry , operating system
In the chemical industry, life science products are considered the most promising markets for the near future. Since pharmaceutical products, food, and fine chemicals are subject to increasingly more complex standards and stricter legal restrictions, efficient methods for the separation of thermally unstable products are needed. Chromatographic separations, for example, usually create the main costs of the overall production process. To realize the full potential of the chromatographic separation, the desired product quality has to be maintained, while operating the process at the economic optimum by reliable and efficient process monitoring and control. For control of batch chromatography, model parameters were estimated and operating parameters were optimized online. The concept has been tested on a laboratory‐scale column with an industrial process control system. Experimental results for a sugar separation are given.