Fuzzy Model for Middle Section of Continuous Line


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The paper presents a methodology for designing a fuzzy model for the middle section of a continuous processing line for tension processing of various materials (sheet metal, tubes, foil, etc.), which is only described by input/output relations. The measured input/output data of the continuous line are the basis for creating its fuzzy model, which can be further applied in the design of a suitable controller and the verification of its properties by simulation. The first part of the paper describes the procedure of the fuzzy model construction; the second part presents the application of the model in the system of the middle section of a continuous processing line. The fuzzy model structure is based on the state space representation of the dynamic system in discrete form. The properties of the fuzzy model were verified by numerical simulation in Matlab. The obtained results have confirmed the rightness of the design method and its applicability to dynamic systems with multiple inputs and outputs.


Edited by:

Tibor Krenicky




P. Fedor and D. Perdukova, "Fuzzy Model for Middle Section of Continuous Line", International Journal of Engineering Research in Africa, Vol. 18, pp. 75-84, 2015

Online since:

October 2015




* - Corresponding Author

[1] L.A. Zadeh, Fuzzy sets, Inform. Control 8 (1965) 338-353.

[2] Y. Bai, Q. Zhuang, Z.S. Roth, Fuzzy logic control to suppress noises and coupling effects in a laser tracking system, IEEE Transactions on Fuzzy Systems 13/1 (2005) 113-121.

DOI: https://doi.org/10.1109/tcst.2004.833653

[3] Baturone, F.J. Moreno-Velo, S. Sanchez-Solano, A. Ollero, Automatic design of fuzzy controllers for car-like autonomous robots, IEEE Transactions on Fuzzy Systems 12/4 (2004) 447-465.

DOI: https://doi.org/10.1109/tfuzz.2004.832532

[4] C.Y. Chang, B.S. Chen, Intelligent robust tracking controls for holonic and nonholonomic mechanical systems using only position measurements, IEEE Transactions on Fuzzy Systems 13/4 (2005) 491-507.

DOI: https://doi.org/10.1109/tfuzz.2004.840125

[5] E. Kim, S. Lee, Output feedback tracking control of MIMO systems using a fuzzy disturbance observer and its application to the speed control of a PM synchronous motor, IEEE Transactions on Fuzzy Systems 13/6 (2005) 725-741.

DOI: https://doi.org/10.1109/tfuzz.2005.859306

[6] S. Kumar, Aof smart volume controllers for consumer electronics, IEEE Transactions Consumer Electronics 51/2 (2005) 600-605.

DOI: https://doi.org/10.1109/tce.2005.1468006

[7] S.E. Shafei, S. Sepasi, Incorporating Sliding Mode and Fuzzy Controller with Bounded Torques for Set-Point Tracking of Robot Manipulators, Elektronika i elektrotechnika 8 (2010) 3-8.

[8] R. Babuška, Fuzzy modeling for control, Kluwer, Boston, (1998).

[9] G. Feng, A survey on analysis nad design of model-based fuzzy control systems, IEEE Transactions on Fuzzy Systems 14/5 (2006) 676-697.

DOI: https://doi.org/10.1109/tfuzz.2006.883415

[10] T.A. Johansen, Fuzzy model based control: Stability robusness and performance issues, IEEE Transactions on Fuzzy Systems 2/1 (1994) 221-233.

DOI: https://doi.org/10.1109/91.298450

[11] K. Kiriakos, Fuzzy model-based control of complex systems, IEEE Transactions on Fuzzy Systems 6/4 (1998) 517-529.

[12] W. Pedrycs, Fuzzy control and fuzzy systems, Research Studies Press, Somerset, UK, (1993).

[13] K. Zeng, N.Y. Zhang, W.L. Xu, A comparative study on sufficient conditions for Tagaki-Sugeno fuzzy sytems as universal approximators, IEEE Transactions on Fuzzy Systems 8/6 (2000) 773-780.

DOI: https://doi.org/10.1109/91.890337

[14] K.S. Tang, K.F. Man, G. Chen, S. Kwong, An optimal fuzzy PID controller, IEEE Transactions Industrial Electronics 48/4 (2001) 757-765.

DOI: https://doi.org/10.1109/41.937407

[15] C.W. Tao, J.S. Taur, Robust fuzzy control for a plant with fuzzy linear model. IEEE Transactions on Fuzzy Systems 13/1 (2005) 30-41.

DOI: https://doi.org/10.1109/tfuzz.2004.839653

[16] P. Fedor, D. Perduková, A DC Drive Fuzzy Model, IJECE – Iranian Journal of Electrical and Computer Engineering 2/1 (2003) 11-16.

[17] P. Brandstetter, M. Dobrovsky, Speed Control of AC Drive with Induction Motor Using Genetic Algorithm, in: Proc. of Int. Joint Conf. CISIS'12 - ICEUTE'12 - SOCO'12, Springer, Book Series: Advances in Intelligent Systems and Computing 189, 2013, pp.341-350.

DOI: https://doi.org/10.1007/978-3-642-33018-6_35

[18] P. Butko, T. Fedor, J. Vittek, Comparison of energy consumption for position controlled PMSM using various energy near-optimal control techniques, in: Proc. of 10th Int. Conf. ELEKTRO 2014, Rajecke Teplice, Slovakia, 2014, pp.268-272.

DOI: https://doi.org/10.1109/elektro.2014.6848900

[19] G. Brandenburg, Ein mathematisches modell fur eine durchlaufende Stoffbahn in einen System angetriebener umschlumgener Walzen. In: Regelungstechnik und Prozess - datenverarbeitung 21/3, 1973, pp.69-104.

DOI: https://doi.org/10.1524/auto.1973.21.112.157

[20] D. Perduková, P. Fedor, Control of a Continuous Line with Incomplete Access to State Variables, Journal of Electrical Engineering 48 (1996) 3-9.