Abstract—In this paper the control of a bioprocess using an adaptive type-2 fuzzy logic controller is proposed. The process is concerned with the aerobic alcoholic fermentation for the growth of Saccharomyces Cerevisiae a n d i s characterized by nonlinearity and parameter uncertainty. Three type-2 fuzzy controllers heve been developed and tested by simulation: a simple type-2 fuzzy logic controller with 49 rules; a type-2 fuzzyneuro- predictive controller (T2FNPC); a t y p e -2 selftuning fuzzy controller ( T2STFC). The T2FNPC combines the capability of the type-2 fuzzy logic to handle uncertainties, with the ability of predictive control to predict future plant performance making use of a neural network model of the non linear system. In the T2STFC the output scaling factor is adjusted on-line by fuzzy rules according to the current trend of the controlled process. T h e advantage of the proposed adaptive algorithms is to greatly decrease the number of rules needed for the control reducing the computational load and at same time assuring a robust control.

Cosenza, B., Galluzzo, M. (2009). Type-2 Fuzzy Control of a Bioreactor. In Proceedings of 2009 - IEEE International Conference on Intelligent Computing and Intelligent Systems (pp.700-704). Beijing : Institute of Electrical and Electronics Engineers, Inc..

Type-2 Fuzzy Control of a Bioreactor

COSENZA, Bartolomeo;GALLUZZO, Mose'
2009-01-01

Abstract

Abstract—In this paper the control of a bioprocess using an adaptive type-2 fuzzy logic controller is proposed. The process is concerned with the aerobic alcoholic fermentation for the growth of Saccharomyces Cerevisiae a n d i s characterized by nonlinearity and parameter uncertainty. Three type-2 fuzzy controllers heve been developed and tested by simulation: a simple type-2 fuzzy logic controller with 49 rules; a type-2 fuzzyneuro- predictive controller (T2FNPC); a t y p e -2 selftuning fuzzy controller ( T2STFC). The T2FNPC combines the capability of the type-2 fuzzy logic to handle uncertainties, with the ability of predictive control to predict future plant performance making use of a neural network model of the non linear system. In the T2STFC the output scaling factor is adjusted on-line by fuzzy rules according to the current trend of the controlled process. T h e advantage of the proposed adaptive algorithms is to greatly decrease the number of rules needed for the control reducing the computational load and at same time assuring a robust control.
Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi Chimici
22-nov-2009
ICIS 2009 - IEEE International Conference on Intelligent Computing and Intelligent Systems
Shanghai, Cina
20-22 Novembre
2009
5
Cosenza, B., Galluzzo, M. (2009). Type-2 Fuzzy Control of a Bioreactor. In Proceedings of 2009 - IEEE International Conference on Intelligent Computing and Intelligent Systems (pp.700-704). Beijing : Institute of Electrical and Electronics Engineers, Inc..
Proceedings (atti dei congressi)
Cosenza, B; Galluzzo, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/57353
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