Parameter Identification For A Class Of Microbial Batch Fermentation Process

The batch fermentation process of glycerol to 1,3-propanediol is complex.Recently,it has obtained the high attention of scholars at home and abroad and has made certain research progress.As the improvement of the scientific research technical level,it is obtained more and more accurate parameters in the models.To minimize the error values of model calculated values and experimental data,the better identification method is chose to solve the parameters according to the characteristic of the models.This paper researches the parameter identification for a class of glycerol microbial batch fermentation process.The main contents and results are as follows:1.According to the parameter identification for a class of microbial batch fermentation process,a new method is proposed.It is based on the methods of B-spline and Tikhonov regularization to estimate the derivatives of experimental values.The optimal parameter values are obtained by using the genetic algorithm,and the calculation results are compared and analyzed.Compared with the existing parameter identification results,it is obtained the smaller slope error and the sum of the slop error and least-square error by using this method.2.According to the parameter identification for a class of microbial batch fermentation process,a two stage method is proposed.Firstly,the original parameter identification optimization models are changed to the simple ones in the first stage.Then the optimal parameter values obtained in the first stage are used to solve the nonlinear equations.And the optimal values of the original parameter identification are obtained.The calculation results show that the better parameter identification results are obtained by using the two stage method.