Parameter Identification in Microbial Continuous Fermentation with Intracellular Substrate and Products

摘要

In this paper, a dynamic system is improved to describe microbial continuous fermentation. Taking the average relative error as the objective function, a parameter identification model is built, the existence of optimal parameters is proved, and the Improved Particle Swarm Optimization (PSO) algorithm is used for solving the optimal parameters. The numerical results show that, the average relative error is cut down by 4.136%~9.248%, and the dynamic system can describe microbial continuous fermentation better.