个人信息Personal Information
副教授
硕士生导师
性别:女
毕业院校:大连理工大学
学位:博士
所在单位:数学科学学院
学科:运筹学与控制论
办公地点:创新园大厦A1014
电子邮箱:xuzhang@dlut.edu.cn
Robust identification of enzymatic nonlinear dynamical systems for 1,3-propanediol transport mechanisms in microbial batch culture
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论文类型:期刊论文
发表时间:2014-04-01
发表刊物:APPLIED MATHEMATICS AND COMPUTATION
收录刊物:SCIE、EI、Scopus
卷号:232
页面范围:150-163
ISSN号:0096-3003
关键字:Nonlinear dynamical system; Robustness analysis; Microorganism batch fermentation; System identification; Optimization algorithm
摘要: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.