SELF ORGANIOZING FUZZY CONTROLLER FOR A NONLINEAR TIME VARYING SYSTEM

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Published: 2006-09-01
DOI: https://doi.org/10.31026/j.eng.2006.03.25

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Omar W. Abdul-Wahab

Abstract

This paper proposes a self organizing fuzzy controller as an enhancement level of the fuzzy controller. The adjustment mechanism provides explicit adaptation to tune and update the position of the output membership functions of the fuzzy controller. Simulation results show that this controller is capable of controlling a non-linear time varying system so that the performance of the system improves so as to reach the desired state in a less number of samples.

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Vol. 12 No. 03 (2006): Journal of Engineering

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Articles
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This work is licensed under a Creative Commons Attribution 4.0 International License.

 
 

How to Cite

“SELF ORGANIOZING FUZZY CONTROLLER FOR A NONLINEAR TIME VARYING SYSTEM” (2006) Journal of Engineering, 12(03), pp. 777–785. doi:10.31026/j.eng.2006.03.25.

References

- Alci, M., Karabiyik, A., and Karatepe, E., “Adaptive fuzzy control of nonlinear systems and comparative analyses,” IJCI Proc. of international Conf. Signal Processing, vol. 1, no. 2, Sep., 2003.

- Daley, S. and Gill, K.F., “Altitude control of a spacecraft using an extended self organizing fuzzy logic controller,” Proc. I. Mech. E., vol. 201, no. 2, pp. 97-106, 1987.

- Jantzen, J., “The self-organizing fuzzy controller”, Tech. Report no. 98-H 869 (soc), 19 Aug 1998.

- Jantzen, J. and Neils K. Poulsen, “Adaptation in the fuzzy self-organizing controller”,http://www.eunite.org/eunite/events/eunite2003/eunite2003-ProgrammeOverview-04-07.pdf.

- Kwong, W. A. and Passino, K. M. “Dynamically focused fuzzy learning control,” IEEE Trans. Syst., Man, Cybern., vol. 26, pp.53-74, Feb. 1996.

- Kwong, W. A., Passsino, K.M. , Lauknonen, E. G. and Yurkovich, S., “ Expert supervision of fuzzy learning systems for fault tolerant aircraft control,” Proc. IEEE, Spec.. Issue Fuzzy Logic Eng. Applicat., vol. 83, pp. 466-483, Mar. 1995.

- Layne, J. R. and Passino, K. M., “Fuzzy model reference learning control,” J. Intell. Fuzzy Syst., vol. 4, no. 1, pp. 33-47, 1996.

- Layne, J., Passino, K and Yurkovich, S. “Fuzzy learning control for antiskid braking systems,” in Proc. IEEE Conf. Decision Contr., Tucson, AZ, Dec. 1992, pp. 2523-2528.

- Lennon, W. and Passino, K., “Intelligent control for brake systems,” in Proc. IEEE Int. Symp. Intell. Contr., Monterey, CA, Aug. 1995, pp. 499-504.

- Passino, K. M. and Yurkovich, S. “Fuzzy control”, Addison Wesley, 1998.

-Procyk, T. and Mamdani, E., “A liguistic self-organizing process controller,” Automatica, vol. 15, no. 1, pp. 15-30, 1979.

-Moudgal, V. G., Kwong, W. A. , Passino, K. M. and Yurkovich, S. “Fuzzy learning control for flexible-link robot,” IEEE Trans. Fuzzy Syst., vol. 3, pp. 199-210, May 1995.

- Tanscheit, R. and scharf, E., “Experiments with the use of a rule-based self-organizing controller for robotics applications,” Fuzzy Sets and Systems, vol. 26, pp.195-214, 1988.

- Zumberge, J. and Passino, K. M., “A case study in intelligent control for a process control experiment,” in Proc. IEEE Int. Symp. Intell. Contr., Dearborn, MI, Sept. 1996, to be published.