个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:能源与动力学院
学科:热能工程. 化学工程. 运筹学与控制论
办公地点:大连理工大学能源与动力学院712室
联系方式:电话:13940865971 邮箱:hcyin@dlut.edu.cn
电子邮箱:hcyin@dlut.edu.cn
Modeling and parameter identification for a nonlinear multi-stage system for dha regulon in batch culture
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论文类型:期刊论文
发表时间:2016-01-01
发表刊物:APPLIED MATHEMATICAL MODELLING
收录刊物:SCIE、EI
卷号:40
期号:1
页面范围:468-484
ISSN号:0307-904X
关键字:Nonlinear multi-stage system; Optimization algorithm; Batch fermentation; System sensitivity
摘要:The bioconversion of glycerol to 1,3-propanediol (1,3-PD) is a complex bioprocess. In this paper, based on biological phenomena of different characteristics at different stages and the genetic regulation of dha regulon, we consider a fourteen-dimensional nonlinear multi-stage dynamic system with unknown time and system parameters for formulating the multi-stage cell growth in batch culture. Some important properties of the multi-stage system are discussed. Our goal is to identify the time and system parameters. To this end, we present a parameter identification problem in which the time and system parameters are decision variables and the cost function measures the discrepancy between experimental data and computational results, subject to the multi-stage system, parameter constraints and continuous state inequality constraints. The system sensitivity (the cost function's gradient, namely, the derivative of the cost function with respect to the time and system parameters), which can be computed by solving an auxiliary initial value problem, can be regarded as the search direction of optimization algorithm. The identification problem is converted into a sequence of nonlinear programming subproblems through the application of the time-scaling transformation, the constraint transcription and local smoothing approximate techniques. Due to the highly complex nature of the identification problem, the computational cost is high. Thus, a parallel algorithm is proposed to solve these subproblems based on the novel combinations of system sensitivity and genetic algorithm. Finally, numerical results show that the multi-stage system can reasonably describe the process of batch culture. (C) 2015 Elsevier Inc. All rights reserved.