尹洪超
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Robust identification of enzymatic nonlinear dynamical systems for 1,3-propanediol transport mechanisms in microbial batch culture
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Indexed by:期刊论文

Date of Publication:2014-04-01

Journal:APPLIED MATHEMATICS AND COMPUTATION

Included Journals:SCIE、EI、Scopus

Volume:232

Page Number:150-163

ISSN No.:0096-3003

Key Words:Nonlinear dynamical system; Robustness analysis; Microorganism batch fermentation; System identification; Optimization algorithm

Abstract:In this paper, in view of glycerol bioconversion to 1,3-propanediol (1,3-PD) by Klebsiella pneumoniae (K. pneumoniae), we study an enzyme-catalytic nonlinear dynamic system with uncertain parameters for formulating the process of batch culture. Some important properties are also discussed. Taking account of the difficulty in accurately measuring the concentrations of intracellular substances and the absence of equilibrium point of the nonlinear system in batch culture, a novel approach is used here to define quantitatively biological robustness of the intracellular substance concentrations for the overall process of batch culture. The purpose of this paper is to identify these uncertain parameters. To this end, taking the defined biological robustness as a performance index, we establish an identification model, which is subject to the nonlinear system. Simultaneously, the existence of optimal solution to the identification model is deduced. We develop an optimization algorithm, based on novel combinations of Nelder Mead algorithm and the change rate of state variable, for solving the identification model under various experiment conditions. The convergence analysis of this algorithm is also investigated. Numerical results not only show that the established model can be used to describe the process of batch culture reasonably, but also imply that the optimization algorithm is valid. (C) 2014 Elsevier Inc. All rights reserved.

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Gender:Male

Alma Mater:大连理工大学

Degree:Doctoral Degree

School/Department:能源与动力学院

Discipline:Thermal Engineering. Chemical Engineering. Operation Research and Control Theory

Business Address:大连理工大学能源与动力学院712室

Contact Information:电话:13940865971 邮箱:hcyin@dlut.edu.cn

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