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Fuzzy modeling and control of biological processes
1Department of Chemical System Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami-shi, Hokkaido 090-8507, Japan. horuichi@betta.chem.kitami-it.ac.jp
Journal of Bioscience and Bioengineering
|October 20, 2005
Summary
Fuzzy modeling and control, using fuzzy set theory, are effective for automating bioprocesses. This review highlights their application in biotechnology, showing promise for complex biological systems.
Area of Science:
- Biotechnology
- Control Engineering
- Computational Intelligence
Background:
- Fuzzy set theory has been applied to biotechnology for two decades.
- Fuzzy modeling and control are increasingly used for biological process automation.
- Experienced operators are crucial for successful bioprocess operation, highlighting the need for advanced control methods.
Purpose of the Study:
- To review recent studies on fuzzy modeling and control of biological processes.
- To summarize, compare, and discuss five industrial applications of fuzzy control in bioprocesses.
- To evaluate the effectiveness of fuzzy control in automating bioprocesses.
Main Methods:
- Literature review of fuzzy modeling and control in biotechnology.
- Comparative analysis of five industrial fuzzy control applications.
- Discussion of system features, control objectives, variables, rule development, and performance.
Main Results:
- Fuzzy control systems demonstrate effectiveness in various industrial biological processes.
- Key aspects like system features, control purpose, and rule development influence fuzzy control performance.
- Fuzzy modeling and control offer a promising approach to bioprocess automation.
Conclusions:
- Fuzzy modeling and control are valuable tools for automating complex bioprocesses.
- These methods can capture the expertise of human operators, enhancing process efficiency and reliability.
- Continued research and application of fuzzy control in biotechnology are warranted.