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Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary
B Andrés-Toro1, J M Girón-Sierra, P Fernández-Blanco
1Department of Computer Architecture and System Engineering, Physical Sciences, Complutense University of Madrid, Spain. deandres@dacya.ucm.es
Journal of Zhejiang University. Science
|March 3, 2004
Summary
Researchers developed a new mathematical model for beer fermentation, optimizing the process using multiobjective evolutionary algorithms and intelligent control for industrial applications.
Area of Science:
- Biotechnology
- Chemical Engineering
- Process Control
Background:
- Industrial beer fermentation is a complex, multiobjective dynamic process.
- Existing mathematical models do not adequately represent realistic industrial conditions.
- Optimizing fermentation requires guiding the process along specific paths.
Purpose of the Study:
- To develop a novel mathematical model for beer fermentation under industrial conditions.
- To optimize the beer fermentation process using advanced computational methods.
- To implement intelligent supervisory control for enhanced fermentation outcomes.
Main Methods:
- Developed a new mathematical model simulating industrial beer fermentation.
- Applied Pareto set approach with multiobjective evolutionary algorithms (MOEAs) for optimization.
- Utilized intelligent control strategies based on defined rules for process supervision.
Main Results:
- Successfully developed a realistic mathematical model for industrial beer fermentation.
- Identified optimal pathways for driving the fermentation process.
- Demonstrated effective optimization and control of the fermentation process.
Conclusions:
- The developed mathematical model accurately represents industrial beer fermentation.
- MOEAs provide an effective method for optimizing complex fermentation processes.
- Intelligent control enhances the supervisory capabilities for beer fermentation.
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