Fuzzy modeling and control of biological processes

Journal of Bioscience and Bioengineering

Volumn 94, Issue 6, 2002, Pages 574-578

  Horiuchi, Jun Ichi ^a  

^a KITAMI INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

Bioprocess; Control; Fermentation; Fuzzy; Industrial application; Modeling

Indexed keywords

FUZZY CONTROL; FUZZY SETS;

FUZZY MODELING;

BIOTECHNOLOGY;

AUTOMATION; BIOPROCESS; BIOTECHNOLOGY; FERMENTATION; METHODOLOGY; MODEL; REVIEW;

EID: 0036968220     PISSN: 13891723     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1389-1723(02)80197-9     Document Type: Review

References (42)

1. Konstantinov, K. B. and Yoshida, T.: Knowledge-based control of fermentation processes. Biotechnol. Bioeng., 39, 479-486 (1992).
2. Zadeh, L. A.: Fuzzy sets. Inform. Cont., 8, 338-353 (1965).
3. Shioya, S., Shimizu, K., and Yoshida, T.: Knowledge based design and operation of bioprocess systems. J. Biosci. Bioeng., 87, 261-266 (1999).
4. Honda, H. and Kobayashi, T.: Fuzzy control of bioprocesses. J. Biosci. Bioeng., 89, 401-408 (2000).
5. Filev, P. D., Kishimoto, M., Sengupta, S., Yoshida, T., and Taguchi, H.: Application of the fuzzy theory to simulation of batch fermentation. J. Ferment. Technol., 63, 545-553 (1985).
6. Dohnal, M.: Fuzzy bioengineering model. Biotechnol. Bioeng., 27, 1146-1151 (1985).
7. Smits, J. P., Janssens, R. J. J., Knol, P., and Bol, J.: Modelling of the glucosinolate content in solid state fermentation of rapeseed meal with fuzzy logic. J. Ferment. Bioeng., 77, 579-581 (1994).
8. Czogala, E. and Rawlik, T.: Modelling of a fuzzy controller with application to the control of biological processes. Fuzzy Set Syst., 31, 13-22 (1989).
9. Jitsufuji, T., Ishikawa, H., Tanaka, H., and Matsushima, K.: A simple method of fuzzy modeling for a microorganism reaction. J. Ferment. Bioeng., 74, 312-319 (1992).
10. Horiuchi, J., Kishimoto, M., and Momose, H.: Hybrid simulation of microbial behavior combining a statistical procedure and fuzzy identification of culture phases. J. Ferment. Bioeng., 79, 297-299 (1995).
11. Hanai, T., Katayama, A., Honda, H., and Kobayashi, T.: Automatic fuzzy modeling for Ginjo sake brewing process using fuzzy neural networks. J. Chem. Eng. Jpn., 30, 94-100 (1997).
12. Tomida, S., Hanai, T., Ueda, N., Honda, H., and Kobayashi, T.: Construction of COD simulation model for activated sludge process by fuzzy neural network. J. Biosci. Bioeng., 88, 215-220 (1999).
13. Kishimoto, M. and Yoshida, T.: Application of fuzzy sets theory to fermentation processes. Hakkokogaku, 69, 107-116 (1991).
14. Tsuchiya, Y., Koizumi, J., Suenari, K., Teshima, Y., and Nagai, S.: Constructions of fuzzy rules and a fuzzy simulation based on the control techniques of Hiroshima Toji (experts). Hakkokogaku, 68, 123-129 (1990).
15. Suenari, K., Tsuchiya, Y., Teshima, Y., Koizumi, J., and Nagai, S.: Performance of sake mash brewing with fuzzy control. Hakkokogaku, 68, 131-136 (1990).
16. Hanai, T., Nishida, T., Ohkusu, E., Honda, H., and Kobayashi, T.: Experimental fermentation of Ginjo sake with two fuzzy controls. Seibutsu-kogaku, 73, 283-289 (1995).
17. 10 fermentation. J. Chem. Eng. Jpn., 24, 94-99 (1991).
18. Nakano, K., Katsu, R., Tada, K., and Matsumura, M.: Production of highly concentrated xylitol by Candida magnoliae under a microaerobic condition maintained by simple fuzzy control. J. Biosci. Bioeng., 89, 372-376 (2000).
19. Shiba, S., Nishida, Y., Park, Y. S., Iijima, S., and Kobayashi, T.: Improvement of cloned α-amylase gene expression in fed-batch culture of recombinant Saccharomyces cerevisiae by regulating both glucose and ethanol concentrations using a fuzzy controller. Biotechnol. Bioeng., 44, 1055-1063 (1994).
20. Park, Y. S., Shi, Z. P., Shiba, S., Cayuela, C., Iijima S., and Kobayashi, T.: Application of fuzzy reasoning on control of glucose and ethanol concentrations in baker's yeast culture. Appl. Microbiol. Biotechnol., 38, 649-655 (1993).
21. Alfafara, C. G., Miura, K., Shimizu, H., Shioya, S., Suga, K., and Suzuki, K.: Fuzzy control of ethanol concentration and its application to maximum gluthathione production in yeast fed-batch culture. Biotechnol. Bioeng., 41, 493-501 (1993).
22. Konstantinov, K. B. and Yoshida, T.: Physiological state control of fermentation processes. Biotechnol. Bioeng., 33, 1145-1156 (1989).
23. Kishimoto, M., Kitta, Y., Takeuchi, S., Nakajima, M., and Yoshida, T.: Computer control of glutamic acid production based on fuzzy clusterization of culture phases. J. Ferment. Bioeng., 72, 110-114 (1991).
24. Takagi, T. and Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control. IEEE Trans. Syst. Man Cybern., SMC-15, 116-132 (1985).
25. Sugeno, T. and Takagi, T.: A fuzzy-logic-based approach to qualitative modeling. IEEE Trans. Fuzzy Syst., 1, 7-31 (1993).
26. Konstantinov, K. B. and Yoshida, T.: An expert approach for control of fermentation processes as variable structure plants. J. Ferment. Bioeng., 70, 48-57 (1990).
27. Kitsuta, Y. and Kishimoto, M.: Fuzzy supervisory control of glutamic acid production. Biotechnol. Bioeng., 44, 87-94 (1994).
28. Horiuchi, J., Kamasawa, M., Miyakawa, H., and Kishimoto, M.: Phase control of fed-batch culture for α-amylase production based on culture phase identification using fuzzy inference. J. Ferment. Bioeng., 76, 207-212 (1993).
29. Horiuchi, J., Kamasawa, M., Miyakawa, H., Kishimoto, M., and Momose, H.: Effective β-galactosidase production by recombinant Escherichia coli based on culture phase identification using fuzzy set theory. J. Ferment. Bioeng., 76, 382-387 (1993).
30. Kishimoto, M., Allsop, P., and Moo-Young, M.: A fuzzy expert system for the optimization of glutamic acid production. Bioprocess Eng., 6, 163-172 (1991).
31. Hanai, T., Kakamu, A., Honda, H., Furuhashi, T., Uchikawa Y., and Kobayashi, T.: Modeling of total evaluation process of Ginjo sake using a fuzzy neural network. Trans. Soc. Inst. Cont. Eng., 32, 1113-1120 (1996).
32. Honda, H., Hanai, T., Katayama, A., Tohyama, H., and Kobayashi, T.: Temperature control of Ginjo sake mashing process by automatic fuzzy modeling using fuzzy neural networks. J. Ferment. Bioeng., 85, 107-112 (1998).
33. Shi, Z. and Shimizu, K.: Neuro-fuzzy control of bioreactor systems with pattern recognition. J. Ferment. Bioeng., 74, 39-45 (1992).
34. Ye, K., Jin, S., and Shimizu, K.: Application of artificial neural network and fuzzy control for fed-batch cultivation of recombinant Saccharomyces cerevisiae. J. Ferment. Bioeng., 81, 412-421 (1996).
35. Matsuura, K., Shiba, H., Hirotsune, M., and Hamachi, M.: Optimizing control of sensory evaluation in the sake mashing process by decentralized learning of fuzzy inferences using a genetic algorithm. J. Ferment. Bioeng., 80, 251-258 (1995).
36. Tanaka, T. and Taya, M.: Reduction in operator supervision time using a modified malfunction detection system with fuzzy inference in an industrial-scale fermentation of alkaline cellulase. J. Biosci. Bioeng., 91, 106-108 (2001).
37. Nakamura, T., Kuratani, T., and Morita, Y.: Fuzzy control application to glutamic acid fermentation, p. 211-215. In Proc. of IFAC Modeling and Control of Biotechnological Processes. IFAC, Noordwijkerhout (1985).
38. Hosobuchi, M., Fukui, F., Suzuki, T., and Yoshikawa, H.: Fuzzy control during microbial production of NL-236B, a precursor of pravastatine sodium. J. Ferment. Bioeng., 76, 482-486 (1993).
39. Ishiguri, H.: Fuzzy control of baker's yeast production, p. 644-651. In Shimizu, K. (ed.), Bioprocess system engineering. Industrial Publishing & Consulting, Tokyo (1994). (in Japanese)
40. Oishi, K., Tominaga, M., Kawato, A., Abe, Y., Imayasu, S., and Nanba, A.: Application of fuzzy control theory to the sake brewing process. J. Ferment. Bioeng., 72, 115-121 (1991).
41. Horiuchi, J. and Kitsuta, Y.: Integrated system for bioprocess monitoring and diagnosis using a local area network. Biotechnol. Tech., 12, 285-288 (1998).
42. 2 production. J. Biosci. Bioeng., 87, 365-371 (1999).