A controller that combines the main characteristics and advantages of three different control methodologies is proposed for the control of systems with nonlinearities and uncertainties. A neural network predictive control approach is implemented modifying the output of a controller with a fuzzy logic structure that uses type-2 fuzzy sets. Neural networks are also used to optimize the membership function parameters. The proposed controller is tested by simulation for the control of a bioreactor characterized by bifurcation and parameter uncertainty.

COSENZA, B., GALLUZZO, M. (2009). Development of a predicitive type-2 neurofuzzy controller. In Chemical Engineering Transactions (pp.1203-1208). MILANO : AIDIC [10.3303/CET0917201].

Development of a predicitive type-2 neurofuzzy controller

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

Abstract

A controller that combines the main characteristics and advantages of three different control methodologies is proposed for the control of systems with nonlinearities and uncertainties. A neural network predictive control approach is implemented modifying the output of a controller with a fuzzy logic structure that uses type-2 fuzzy sets. Neural networks are also used to optimize the membership function parameters. The proposed controller is tested by simulation for the control of a bioreactor characterized by bifurcation and parameter uncertainty.
Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi Chimici
11-mag-2009
ICheaP-9 - 9th International Conference on Chemical and Process Engineering
Roma
10-13 maggio 2009
9
2009
6
COSENZA, B., GALLUZZO, M. (2009). Development of a predicitive type-2 neurofuzzy controller. In Chemical Engineering Transactions (pp.1203-1208). MILANO : AIDIC [10.3303/CET0917201].
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/10447/57359
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