Release Time:2019-03-09  Hits:

Indexed by: Journal Article

Date of Publication: 2012-01-01

Journal: INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS

Included Journals: SCIE

Volume: 89

Issue: 10

Page Number: 1426-1444

ISSN: 0020-7160

Key Words: continuous culture; nonlinear dynamical system; biological robustness; metabolic system identification; IPSO algorithm

Abstract: 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.