Satisfactory Optimization Method for Glutamic Acid Fermentation Process

被引:0
作者
Guan Shouping [1 ]
Yin Xiaofeng [1 ]
Fang Shaochun [1 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China
来源
PROCEEDINGS OF THE 2012 24TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2012年
关键词
Satisfactory optimization; Glutamic acid fermentation; Genetic algorithm; Multi-objective optimization;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, the dynamic model of the glutamic acid fermentation process is established by using the neural network. Combined with satisfaction optimization method, multi-objective and multi-variable optimization for the glutamic acid fermentation process is proceeded with the objects of the production rate of glutamic acid and conversion rate. The paper also set up the corresponding satisfaction function for all the objects, and constructed the satisfactory optimization model for glutamic acid fermentation process. In order to realize the whole process optimization, the trajectories of operation variables in each hour from start to finish and the beginning and end moment are treated as the optimization variables, combined with the real-coding genetic algorithm to proceed the multi-objective optimization. Although the above optimizing methods for two objectives can't guarantee to obtain the process optimal solutions, but can achieve the satisfactory results to decision maker.
引用
收藏
页码:2894 / 2898
页数:5
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