Adaptive fuzzy control applied to a fermentation system of continuous alcohol flow
DOI:
https://doi.org/10.17533/udea.redin.14604Keywords:
controller, fuzzy logic, adaptive control, inference, inverse model, strategy of tuning, learningAbstract
The FRMLC, Fuzzy Reference Model Learning Control has been studied as a method for tuning fuzzy controllers. Its performance has been evaluated in a fermentation system with continuous alcohol fl ow which is characterized as a non lineal dynamics. Parameters vary with time in non lineal dynamics. A method of innovative tuning was employed which implicates a Matlab development that facilitates the study of the control technique FRMLC. It allowed building tuning methodologies for the application of that technique in different processes.
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References
K. Passino, S. Yurkovich. Fuzzy control. Ed. AddisonWesley. California. USA. 1998. pp. 522-532.
G. Muñoz Quiñones, J. Ballén Salamanca. Diseño e implementación de un controlador difuso autosintonizado sobre microcontroladores, aplicado al control del péndulo invertido. Trabajo de pregrado. Universidad Distrital. Bogotá. 2003. pp. 68-89.
P. Antsaklis, K. Passino. An introduction to intelligent and autonomous control. Ed. Kluwer Academic Publishers. Norwell (USA). 1993. pp. 427-452.
W. Li-Xin. A course in fuzzy systems and control. Ed. Prentice Hall. New Jersey (USA). 1997. pp. 424-476.
R. L. Jeffey. “Fuzzy reference model learning control”. Journal of Intelligent and Fuzzy Systems. Vol.4-1. 1996. pp. 33-47. DOI: https://doi.org/10.3233/IFS-1996-4103
S. Abhishek. A multi-scale approach to fed-batch bioreactor control. Tesis de Maestria. Universidad de Pittsburgh. Pennsylvania (USA). 2002. pp. 71-88.
A. Kwong, M. Passino. “Dynamically focused fuzzy learning control”. IEEE transactions on system man and cybernetics. Vol. 26. 1996. pp. 53-74. DOI: https://doi.org/10.1109/3477.484438
L. Zadeh. The birth and evolution of fuzzy logic (FL), soft computing (SC) and computing with words (CW): a personal perspective. Ed. World Scientifi c Publishing Co. New Jersey (USA). 1996. pp. 819-843. DOI: https://doi.org/10.1142/9789814261302_0044
P. Dadone. Design optimization of fuzzy logic systems. Tesis de Doctorado. Virginia Polytechnic Institute and State University. Blacksburg. VA. 2001. pp. 64-97.
R. L. Jeeffey, K. Passino, S. Yurkovich. “Fuzzy learning control to antiskid braking system”. IEEE transactions on control. Vol.1-2. 1993. pp. 122-129. DOI: https://doi.org/10.1109/87.238405
K. Tanaka, H. Wang. Fuzzy control system design and analysis. Ed. Jhon Wiley & Sons. New York (USA). 2001. pp. 320-361.
J. Mendel. “Fuzzy logic system for engineering: a tutorial”. Proceeding of the IEEE. Vol. 83. 1995. pp. 345-377. DOI: https://doi.org/10.1109/5.364485
I. Queinnec, B. Dahhou, Y. Sevely. “Theoretical and experimental results in optimization of fedbatch fermentation process”. Journal of Systems Engineering. Vol.1. 1991. pp. 31-40.
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