The sensitivity properties of a linear system affected by parameter variations can be studied by means Of properly defined linear subspaces of the state space. Summary--In this paper a new approach to the study of parameter insensitivity of a linear, time-varying, continuous and finite-dimensional
A new approach to bioconversion reaction kinetic parameter identification
✍ Scribed by Bing H. Chen; Edward G. Hibbert; Paul A. Dalby; John M. Woodley
- Publisher
- American Institute of Chemical Engineers
- Year
- 2008
- Tongue
- English
- Weight
- 368 KB
- Volume
- 54
- Category
- Article
- ISSN
- 0001-1541
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✦ Synopsis
Abstract
The commonly used methods for bioconversion kinetic parameter identification are linear plotting and nonlinear regression. However, linear plotting methods generally require considerable experimentation, and nonlinear regression can lead to “local optimization” because the obtained parameters depend heavily on given initial values. In this article, a new and reliable nonlinear regression‐based approach to bioconversion kinetic parameter estimation is reported. By obtaining preliminary values of kinetic parameters on a step‐by‐step basis, the number of estimated parameters in each step can be reduced to 3 or 4. These preliminary values can then be used as initial guesses for the final parameter estimation via nonlinear regression. Compared with the linear plotting method, the proposed approach can significantly reduce the number of experiments required for kinetic parameter estimation. The transketolase catalyzed synthesis of 1,3‐dihydroxypentan‐2‐one from propionaldehyde and β‐hydroxypyruvate is used as an experimental example to illustrate the approach. © 2008 American Institute of Chemical Engineers AIChE J, 2008
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