Title :
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
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;
Conference_Titel :
Control Engineering and Communication Technology (ICCECT), 2012 International Conference on
Conference_Location :
Liaoning
Print_ISBN :
978-1-4673-4499-9
DOI :
10.1109/ICCECT.2012.94
