The application of fuzzy control to fed-batch fermentation

 

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dc.contributor.advisor Swartz, C L E en_ZA
dc.contributor.author Hadley, Trevor Deon en_ZA
dc.date.accessioned 2016-09-06T14:45:48Z
dc.date.available 2016-09-06T14:45:48Z
dc.date.issued 1995 en_ZA
dc.identifier.citation Hadley, T. 1995. The application of fuzzy control to fed-batch fermentation. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/21700
dc.description Bibliography: pages 101-105. en_ZA
dc.description.abstract Fermentation processes are highly nonlinear and subject to variability. The fermentation's states are not readily available on-line and therefore the application of closed loop control schemes have been hindered. It was decided to investigate fuzzy control as it is able to deal with systems whose operation does not easily fit into the mathematical framework of traditional control approaches such as fermentations where the systems are highly nonlinear. The fermentation of lysine is an emergent industry in South Africa and it was therefore decided to focus on this fermentation. The control of penicillin fermentation was also investigated as it closely resembles the fermentation of lysine. A review of the types of control and estimation techniques used in the literature for biosystems was done to assess state of art in biocontrol. This covered optimal control techniques, neural networks, fuzzy controllers and adaptive control techniques. The operation and properties of fuzzy controllers were investigated. A specific form of fuzzy controller, presented in the literature, which was shown to correspond to a PI controller with a nonlinear gain was discussed. The effect of the number of output sampling points was analysed and it was found that the number of output sampling points used has an effect on the output and input response. It was also found that a higher number of sampling points results in a nonlinear integral constant and a non linear gain which has more resolution. The fuzzy controller's output response equations were found to be of a PI form with a possible bias term irrespective of the number of sampling points. The fuzzy controller was shown to yield better output and input response to that of an equivalently tuned linear PI controller for a first, second and third order system because it is able to take advantage of its nonlinear form. It was also shown that it is possible to obtain less severe input action for relatively the same value of SSE (sum of squared errors) when a higher number of sampling points is used for a first order system with dead time. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Chemical Engineering en_ZA
dc.title The application of fuzzy control to fed-batch fermentation en_ZA
dc.type Master Thesis
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Engineering and the Built Environment
dc.publisher.department Department of Chemical Engineering en_ZA
dc.type.qualificationlevel Masters
dc.type.qualificationname MSc (ChemEng) en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Hadley, T. D. (1995). <i>The application of fuzzy control to fed-batch fermentation</i>. (Thesis). University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Chemical Engineering. Retrieved from http://hdl.handle.net/11427/21700 en_ZA
dc.identifier.chicagocitation Hadley, Trevor Deon. <i>"The application of fuzzy control to fed-batch fermentation."</i> Thesis., University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Chemical Engineering, 1995. http://hdl.handle.net/11427/21700 en_ZA
dc.identifier.vancouvercitation Hadley TD. The application of fuzzy control to fed-batch fermentation. [Thesis]. University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Chemical Engineering, 1995 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/21700 en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Hadley, Trevor Deon AB - Fermentation processes are highly nonlinear and subject to variability. The fermentation's states are not readily available on-line and therefore the application of closed loop control schemes have been hindered. It was decided to investigate fuzzy control as it is able to deal with systems whose operation does not easily fit into the mathematical framework of traditional control approaches such as fermentations where the systems are highly nonlinear. The fermentation of lysine is an emergent industry in South Africa and it was therefore decided to focus on this fermentation. The control of penicillin fermentation was also investigated as it closely resembles the fermentation of lysine. A review of the types of control and estimation techniques used in the literature for biosystems was done to assess state of art in biocontrol. This covered optimal control techniques, neural networks, fuzzy controllers and adaptive control techniques. The operation and properties of fuzzy controllers were investigated. A specific form of fuzzy controller, presented in the literature, which was shown to correspond to a PI controller with a nonlinear gain was discussed. The effect of the number of output sampling points was analysed and it was found that the number of output sampling points used has an effect on the output and input response. It was also found that a higher number of sampling points results in a nonlinear integral constant and a non linear gain which has more resolution. The fuzzy controller's output response equations were found to be of a PI form with a possible bias term irrespective of the number of sampling points. The fuzzy controller was shown to yield better output and input response to that of an equivalently tuned linear PI controller for a first, second and third order system because it is able to take advantage of its nonlinear form. It was also shown that it is possible to obtain less severe input action for relatively the same value of SSE (sum of squared errors) when a higher number of sampling points is used for a first order system with dead time. DA - 1995 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 1995 T1 - The application of fuzzy control to fed-batch fermentation TI - The application of fuzzy control to fed-batch fermentation UR - http://hdl.handle.net/11427/21700 ER - en_ZA


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