Title :
Hybrid modeling in glutamic acid fermentation process
Author :
Wang Guicheng ; Chunlong, Zhang ; Changliang, Guan ; Zhixin, Ren ; Zhang Zhansheng ; Jinna, Li
Author_Institution :
Shenyang Univ. of Chem. Technol., Shenyang, China
Abstract :
Studying the kinetic model and neural network model combining hybrid modeling of glutamic acid fermentation process, hybrid model consists of two parts, one is the mechanism model, through reasonable assumptions and limitations, simplifying the kinetics of biochemical reaction process, it is basis of hybrid model, describes the basic characteristics of glutamic acid fermentation process; the other part is a neural network model, using neural network training function of knowledge, and establishing glutamic acid fermentation process between the input and output mapping, this mapping only depends on the actual production data, and has nothing to do with the actual process, it is a secondary part of the hybrid model for correction kinetic model. Through simulation, respectively, glutamic acid fermentation process kinetic model and hybrid model to compare the results to prove the value of hybrid model predictions closer to the system actual output, the model is more accurate.
Keywords :
biochemistry; chemical reactions; fermentation; neural nets; production engineering computing; biochemical reaction process kinetics; glutamic acid fermentation process; hybrid modeling; kinetic model; mechanism model; neural network model; neural network training function; Biological system modeling; Data models; Equations; Kinetic theory; Mathematical model; Microorganisms; Neural networks; Glutamic Acid Fermentation Process; Hybrid Modeling; Kinetic Model; Neural Network;
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
DOI :
10.1109/CCDC.2012.6244393