| Co-Investigator(Kenkyū-buntansha) |
OMASA Takeshi Osaka University, Biotechnology, Assistant Professor, 大学院・工学研究科, 助手 (00252586)
KATAKURA Yoshio Osaka University, Biotechnology, Assistant Professor, 大学院・工学研究科, 助手 (50263207)
菅 健一 大阪大学, 大学院・工学研究科, 教授 (20029250)
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| Budget Amount *help |
¥3,100,000 (Direct Cost: ¥3,100,000)
Fiscal Year 2002: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2001: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 2000: ¥2,000,000 (Direct Cost: ¥2,000,000)
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| Research Abstract |
The objective of the research is the development of Fuzzy control system, which include the know-how of the superior fermentation technique, and is suitable for the production of Insulin by Saccharomyces cerevisiae. Insulin is important pharmaceuticals for diabetes, and produced mainly abroad, for example, Novo. Co. Ltd in Denmark has been producing Insulin using yeast However, we can easily imagine the severe technical problems in the production, because yeast produce alcohol, which seriously effect on the cell growth and the production. There fore, we need to perform many culture experiment in order to develop the fuzzy control algorithm and the on-line control system.
In order to make sure the validity of the fuzzy control system, we tried to use the control system in the alcohol production by Saccharomyces cerevisiae. We succeeded to control the glucose feeding and to increase the growth rate and shorten culture time for the alcohol production. Our fuzzy control has a simple structu
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re of fuzzy rules and membership functions compared with the normal fuzzy control, which has been developed in Japanese sake brewery company. Our approach applied to the immobilized cell system for alcohol production, and we can keep the glucose concentration at suitable level for the ethanol production successfully. In the fuzzy control, we have a severe problem which is the manual tuning of membership functions and manual adjustment of production rules, because we spend a lot of trouble for the procedures and they influence the efficiency of the fuzzy control serious ly. Then we tried to make the display system which shows the membership functions causing the fuzzy reasoning error. Taking into consideration of the suggestion from the display system, we modified the membership function. If the modification is small, the fuzzy control usually improved a little bit. But, if modified largely, the fuzzy control is damaged, because the many rule, which is not considered into the modification effect was effected by the modification. We also investigate the use of the proteome analysis technique for the fuzzy control development. Now, 2-D electrophoresis gel image is not stable but we succeed it to distinguish the culture state with the aid on ANN. Therefore we will be able to use the information from proteome analysis for the development of fuzzy control system. Less
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