DocumentCode :
3304893
Title :
Modeling in microbial batch culture and its parameter identification
Author :
Gong, Zhaohua ; Liu, Chongyang ; Feng, Enmin
Author_Institution :
Sch. of Math. & Inf. Sci., Shandong Inst. of Bus. & Technol., Yantai, China
fYear :
2009
fDate :
15-18 Dec. 2009
Firstpage :
6213
Lastpage :
6217
Abstract :
In this paper, the nonlinear dynamical system of batch fermentation is investigated in the bioconversion of glycerol to 1,3-propanediol (1,3-PD) by Klebsiella pneumoniae. Taking account of the kinetic behavior and experimental results in the batch cultures, we propose a two-stage dynamical system to formulate the fermentation process. Then some properties of the proposed system are proved. In view of the big errors between observations and numerical simulation results, we subsequently establish a parameter identification model to identify parameters in the system. The identifiability of the model is also discussed. Finally, in order to find the optimal parameters of the identification model, an improved simulated annealing algorithm combined with Hook-Jeeves local search is constructed. Numerical results show that the two-stage system can describe the factual fermentation better and the optimization algorithm is valid.
Keywords :
fermentation; nonlinear dynamical systems; numerical analysis; parameter estimation; simulated annealing; Hook Jeeves local search; Klebsiella pneumoniae; batch fermentation; glycerol bioconversion; microbial batch culture modeling; nonlinear dynamical system; numerical simulation; parameter identification; simulated annealing algorithm; Biomass; Costs; Environmentally friendly manufacturing techniques; Inductors; Kinetic theory; Nonlinear dynamical systems; Numerical simulation; Parameter estimation; Production; Simulated annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
Conference_Location :
Shanghai
ISSN :
0191-2216
Print_ISBN :
978-1-4244-3871-6
Electronic_ISBN :
0191-2216
Type :
conf
DOI :
10.1109/CDC.2009.5400148
Filename :
5400148
Link To Document :
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