Fuzzy logic control Fuzzy logic control means using a smart mechanism to convert the control rules devised by the operator into the control system. It makes it possible to transfer the operator experience into automatic control systems. This kind of control provides an excellent opportunity to consider uncertainties and inaccuracies in process control. It uses
Authors & references
Professor Emeritus Kauko Leiviskä, University of Oulu
Zadeh, L. A. (1965). Fuzzy Sets. Information and Control 8(3):338-353.
Zadeh, L. A. (1973). Outline of a new approach to the analysis of complex systems and decision processes. IEEE Transactions on Systems, Man and CyberneticsSMC-3(1):28–44.
Mamdani, E.H. (1974). Application of fuzzy algorithms for control of simple dynamic plant. Proceedings of the Institution of Electrical Engineers 121(12):1585–1588.
Holmblad, L. and Ostergaard, J. (1981). Control of a cement kiln by fuzzy logic techniques. IFAC Proceedings Volumes 14(2):809-814.
Wakami N. (1994). Fuzzy control and neural networks: Applications for consumer products. In: Driankov D., Eklund P.W., Ralescu A.L. (eds) Fuzzy Logic and Fuzzy Control. IJCAI 1991. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence), vol 833. Springer, Berlin, Heidelberg.
Hirota. K. (2012). Industrial Applications of Fuzzy Technology. Springer Science & Business Media, 312 p.
Shen, L. (1997). Fuzzy logic control ASIC chip. Journal of Computer Science & Technology 12(3):263-270.
Serrano-Gotarredona T., Linares-Barranco B. and Andreou A.G. (1998). Analog Learning Fuzzy ART Chips. In: Adaptive Resonance Theory Microchips. The Springer International Series in Engineering and Computer Science, Vol. 456. Springer, Boston, MA.
Alcala-Fdez, J. and Alonso, J.M. (2016). A Survey of Fuzzy Systems Software: Taxonomy, Current Research Trends, and Prospects. IEEE Transactions on Fuzzy Systems 24(1):40-56. [Online 9 Available from: http://dx.doi.org/10.1109/TFUZZ.2015.2426212 [Accessed 9th March 2020].
Precup, R.-E. and Hellendoorn, H. (2011). Industrial Applications of Fuzzy Control. Computers in Industry 62(3):213-226.
Rajpoot, S. (2014). Design and Development of Fuzzy Logic Controller for Consistency Control of Pulp. International Journal of Enhanced Research in Science Technology & Engineering 3(7):232-239.
Jain, A., Bansal, M. C. and Mukherjee, S. (2009). Fuzzy modeling and control of basis weight of paper using Simulink. Proceedings of the 10th WSEAS international conference on Fuzzy systems, pp. 97-103.
Juuso, E., Järvensivu, M. and Ahava, O. (2001). Intelligent Supervisory Control of an Industrial Rotary Kiln. In: Leiviskä K. (editor) Industrial Applications of Soft Computing. Paper, Mineral and Metal Processing Industries. Physica-Verlag, Heidelberg, New York. pp. 175-196. ISSN 1434-9922.
Belarbi, K,, Bettou, K. and Mezaache, A. (2000). Fuzzy neural networks for estimation and fuzzy controller design: simulation study for a pulp batch digester. Journal of Process Control 10(1):35-41.
Lampela, K., Kuusisto, L. aand Leiviskä, K. (1996). D100-stage bleaching control with fuzzy logic. Tappi J. 79(4):93-97.
Achiche, S., Baron, L., Balazinski, M. and Benaoudia, M. (2007). Online prediction of pulp brightness using fuzzy logic models. Engineering Applications of Artificial Intelligence 20(1):25-36.
Paiva, R.P., Dourado, A. and Duarte, B (2004). Quality prediction in pulp bleaching: application of a neuro-fuzzy system Control Engineering Practice 12:587–594.
Myllyneva, J., Leiviskä, K., Kortelainen, J. and Nystedt, H. (1997). Fuzzy Control of Thermomechanical Pulping. Proceedings of 1997 International Mechanical Pulping Conference. Stockholm, 9-13 June. pp. 381-384.
Castro, J.J. and Doyle, F.J. (2002). Plantwide Control of the Fiber Line in a Pulp Mill. Industrial and Engineering Chemistry Research 41(5):310–1320.
Driankov, D.; Hellendoorn, H.; Reinfrank M. (1993). An Introduction to Fuzzy Control. Springer, Berlin. 316 p.
Wang, L.-X. (1994). Adaptive Fuzzy Systems and Control, Design and Stability Analysis. Prentice Hall, Englewood Cliffs, New Jersey.
Zimmermann, H. J. (1991). Fuzzy Set Theory — and its Applications. 2nd Edition. Kluwer Academic Publishers, Boston. 399 p.
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