DocumentCode :
1672980
Title :
Research on hybrid adaptive fuzzy control for the fermentation process
Author :
Guan, Shouping ; Zhang, Xin ; Jia, Suna
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear :
2010
Firstpage :
3590
Lastpage :
3595
Abstract :
A multi-variable dynamic model of the glutamic acid fermentation process based on neural network is established. Combining the off-line Optimal control method and the on-line adaptive fuzzy neural network control method, the hybrid fuzzy adaptive fermentation process control model is designed. The off-line optimization track is the main control model, while the adaptive fuzzy neural network based on the genetic algorithm as the assist-control model to modify its output on-line. The simulation results show that application of hybrid fuzzy adaptive controller can effectively overcome all sorts of interference in the fermentation process to ensure a higher rate of acid production.
Keywords :
adaptive control; fermentation; fuzzy control; fuzzy neural nets; multivariable control systems; optimal control; fermentation process; genetic algorithm; glutamic acid fermentation; hybrid adaptive fuzzy control; multivariable dynamic model; neural network; optimal control method; optimization track; Adaptation model; Artificial neural networks; Biomass; Fuzzy control; Fuzzy neural networks; Optimization; Process control; fuzzy neural network; genetic algorithm; glutamic acid fermentation; hybrid control model; optimal control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
Type :
conf
DOI :
10.1109/WCICA.2010.5553886
Filename :
5553886
Link To Document :
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