Parameters Identification And Analysis Of Nonlinear Dynamics System In Microbial Continuous Cultures

A five-dimensional nonlinear dynamic system, which describes the process of glycerol microorganism fermentation in continuous culture, is studied in this dissertation. According to the features and the dynamic behaviors of the fermentation process, we study some properties of this system in theory. Then we propose a new model to describe the genetic regulation of dha regulon in the reductive pathway of glycerol fermentation. The study of the new model can not only be helpful for deeply understanding metabolic and genetic regulation of dha regulon of glycerol metabolism, but also provide certain reference for genetic modification of Klebsiella pneumoniae. This work was supported by the tenth 5 years' projects of Science and Technology Administration of China " Microbial Production of 1,3-Propanediol " (No. 2001BA708B01-04) and the National High Technology Research and Development Program of China (863 Program) " Biodiesel and 1,3-Propanediol Integrated Production " (No. 2007AA02Z208). The main results obtained in this dissertation may be summarized as follows:1. The properties of the five-dimensional system are discussed qualitatively. Existent condition of equilibrium points for the system is deduced and an algorithm is constructed to compute equilibriums for given dilution rate and substrate concentration in feed medium. Through the computation of the equilibriums by fixing dilution rate but varying substrate concentration in feed medium, we confirm the existence of multiple steady states. The stability of the system is also investigated in theory. The results are in accordance with the phenomena of multiple steady states and bifurcation which have been observed in the experiments.2. The reductive pathway and the genetic regulation of glycerol fermentation are analyzed. Basing on the analysis, we build a genetic regulating dynamic system. Then we discuss some basic properties of the system, such as existence and uniqueness of the solution to the system. Moreover, we build an optimization model to identify the parameters of the system. At last, an algorithm is constructed to solve the parameters identification problem.