Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms

被引：32
作者：
Andres-Toro, B. [1 ]
Giron-Sierra, J.M. [1 ]
Fernandez-Blanco, P. [1 ]
Lopez-Orozco, J.A. [1 ]
Besada-Portas, E. [1 ]
机构：
[1] Dept. of Comp. Arch. and Syst. Eng., Complutense Univ., Madrid
来源：
Journal of Zhejiang University: Science | 2004年 / 5卷 / 04期
关键词：
Fermentation processes; Genetic algorithms; Industrial control; Multiobjective optimization; Multivariable control systems;
D O I：
10.1631/jzus.2004.0378
中图分类号：
学科分类号：
摘要：
This paper describes empirical research on the model, optimization and supervisory control of beer fermentation. Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results. The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs). Successful finding of optimal ways to drive these processes were reported. Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules.
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收藏
页码：378 / 389
页数：11
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