Parameter Identification in Microbial Continuous Fermentation with Intracellular Substrate and Products

Author

Mingmin Jiao ; Xiaohong Li ; Enmin Feng

Author_Institution

Coll. of Sci., Univ. of Sci. & Technol. LiaoNing, Anshan, China

fYear

2012

fDate

7-9 Dec. 2012

Firstpage

205

Lastpage

209

Abstract

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.

Keywords

fermentation; microorganisms; particle swarm optimisation; PSO; average relative error; dynamic system; improved particle swarm optimization; intracellular products; intracellular substrate; microbial continuous fermentation; optimal parameters; parameter identification; Educational institutions; Kinetic theory; Mathematical model; Optimization; Parameter estimation; Particle swarm optimization; Substrates; PSO; microbial continuous fermentation; parameter identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Engineering and Communication Technology (ICCECT), 2012 International Conference on

Conference_Location

Liaoning

Print_ISBN

978-1-4673-4499-9

Type

conf

DOI

10.1109/ICCECT.2012.94

Filename

6414119