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论文类型：期刊论文
发表时间：2012-01-01
发表刊物：INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS
收录刊物：SCIE
卷号：89
期号：10
页面范围：1426-1444
ISSN号：0020-7160
关键字：continuous culture; nonlinear dynamical system; biological robustness; metabolic system identification; IPSO algorithm
摘要：To date, there still exist some uncertain factors in the continuous fermentation of glycerol to 1,3-Propanediol 91,3-PD) by Klebsiella pneumoniae because of the limitation in bio-techniques. In this paper, among these uncertain factors, we aim to infer the transport mechanisms of the substrate and the product across the cell membrane of the biomass. On the basis of different inferences of transport mechanisms, we reconstruct various metabolic systems and develop their dynamical systems. To determine the most reasonable metabolic system from all possible ones, we give a quantitative definition of biological robustness and propose an identification model on this basis. An improved Particle Swarm Optimization algorithm is developed to solve the identification model. Numerical results show that the identified system can describe the fermentation process well. Furthermore, to maximize the concentration of 1,3-PD, an optimization model is proposed. Numerical results show that the concentration of 1,3-PD can be increased considerably by employing the obtained optimal strategy.