| The batch and continuous fermentation of bio-dissimilation of glycerol to 1,3-propane-diol (1,3-PD) by Klebsiella pneumoniae(K.pneumoniae) are investigated in this paper. Basing on enzyme-catalytic kinetic model of glycerol metabolism in K.pneumoniae on the reductive pathway, we develop the nonlinear hybrid dynamical system to describe batch and continuous fermentation of glycerol according to different transport mechanisms of 1,3-PD, in which the inhibitory effect of 3-hydroxypropionaldehyde(3-HPA) on the growth of biomass was taken into consideration, and the properties of systems are studied. On the basis of the quantitative definition of biological robustness, we establish a nonlinear hybrid dynamical system identification model. Finally, we construct a parallel algorithm to solve the identification model, and infer the transport mechanism of 1,3-PD by numerical parallel computing. The research can not only develop the nonlinear hybrid dynamical system, parallel computing and parallel optimization algorithm, but also be helpful for deeply understanding metabolism pathways of glycerol fermentation by K.pneumoniae. In addition, this work is supported by National Natural Science Foundation "Optimization theory and algorithm of nonsmooth dynamic system in a class of complex networks" (No. 10871033) and the National High Technology Research and Development Program(863 Program) "Biodiesel and 1,3-Propanediol Integrated Production" (No.2007AA02Z208). The main results in this dissertation may be summarized as follows:1. Basing on batch and continuous fermentation of bio-dissimilation of glycerol to 1,3-PD by K.pneumoniae, we propose the nonlinear hybrid dynamical systems on the basis of three transport mechanisms of 1,3-PD. In this dissertation, considering the inhibitory effect of 3-HPA on the growth of biomass and assuming that the glycerol transported by active transport coupled with passive diffusion, we aim to infer the most reasonable one from three possible transport mechanisms of 1,3-PD across the cell membrane (ac-tive transport, passive diffusion or active transport coupled with passive diffusion), and develop the corresponding nonlinear hybrid dynamical system to describe batch and con-tinuous fermentation of glycerol. It is proved that the solution to the system uniquely exists and is continuous with respect to parameters.2. Because of lack of intracellular information, we propose a quantitative definition of biological robustness. Presenting a performance index on the basis of the average relative error of extracellular substance concentrations and the biological robustness, we establish an identification model containing discrete and continuous parameters, which is subject to some conditions including the proposed nonlinear hybrid dynamical systems, the ap-proximately steady state of the dynamical system. Finally, we prove the identifiability and existence of the optimal solution of the identification model.3. A numerical computation algorithm is constructed to solve the nonlinear hybrid dynamical systems identification model. Because the performance index and constraint condition are nonlinear functional with respect to parameters, we cannot obtain analytic solutions for the identification model. The model is numerically solved by randomly generating large number of sample points from the admissible set of parameters. On the one hand, we construct a serial algorithm to solve the identification model, but the serial algorithm requires a large computation amount and time, and its computing is inefficient when the number of sample is larger. On the other hand, in order to improve computation efficiency, we present a parallel algorithm to solve the identification model by the parallel computing, and develop its parallel program using MPI which runs on the lenovo 1800 cluster of school of mathematical sciences from dalian university of technology. Numerical results show that it is most reasonable that 1,3-PD pass the cell membrane by active transport coupled with passive diffusion, and the identification problem is solved more quickly and efficiently by parallel computing.
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