Modeling and optimization control of vitamin B12 fermentation process

The fermentation parameters are not usually optimal, which easily lead to low fermentation unit and high output fluctuation. Therefore, the aim of this article is to develop a method of how to find the optimal trajectories of fermentation parameters. Vitamin B-12 is a necessity for human body and animal, however, at the present, it is produced with low output and expensive price; as a result, it is cried for increasing output. Optimization can be obtained through precise mathematic model, however due to the complexity and high non-linearity of fermentation process, most simple mathematical models cannot describe the characteristic of bio-systems very, well. The microbial fermentation usually goes step by step. The best operating conditions of each step are different; so the optimization of each step needs to be. sought respectively. This paper founded respectively neural network models, which are able to realize multi-step pre-estimate, for the biomass concentration, the substrate concentration, and the product concentration of Vitamin B-12 fermentation process. Based on the models, genetic algorithm gained the optimal control trajectories of fermentation temperature and pH by setting different objective functions in different fermentation phases to seek optimization. Putting the optimal operating conditions into practice makes the fermentation unit an obvious increase.