AN ADAPTIVE SLIDING-MODE FUZZY CONTROL (ASMFC) APPROACH FOR A CLASS OF NONLINEAR SYSTEMS

Jian-Hua Zhang, Johann F. Böhme

2004

Abstract

This paper uses the concept of sliding-mode control (SMC), as a special approach in nonlinear control theory, in aiding the design of a fuzzy controller. The mathematical specifics of the presented approach are given along with its performance analysis. It was concluded that the new approach with distinctive characteristics holds potential for coping with difficult control problems for a class of complex (generally nonlinear) systems.

References

1. Chen, Y.-Y. and T.-C. Tsao, 1989. A description of the dynamic behavior of fuzzy systems, IEEE Trans. Syst. Man and Cybernet., vol. 19 (4), pp. 745-755.
2. Driankov, D., H. Hellendoorn, and M. Reinfrank, 1993. An introduction to fuzzy control, Springer-Verlag, Berlin/New York/Heidelberg.
3. Hoffmann, F. and O. Nelles, 2001. Genetic programming for model selection of TSK-fuzzy systems, J. of Information Sciences, vol. 136 (4), pp. 7-28.
4. Hung, J.Y., W. Gao and J.C. Hung, 1993. Variable structure control: a survey, IEEE Transactions on Industrial Electronics, vol. 40 (1), pp.2-21.
5. Hwang, G.-C. and S.-C. Lin, 1992. A stability approach to fuzzy control design for nonlinear system, Fuzzy Sets and Systems, vol. 48, pp.279-287.
6. Jang, J.-S. R., 1992a. Self-learning fuzzy controllers based on temporal back propagation, IEEE Trans. Neural Net., vol. 3 (5), pp. 714-723.
7. Jang, J.-S. R., 1992b. Neuro-fuzzy modeling: architecture, analyses and applications, Ph.D. dissertation, Department of Electrical Engineering and Computer Science, University of California Berkeley, Berkeley, CA.
8. Jang, J.-S. R., 1993. ANFIS: adaptive-network-based fuzzy inference systems, IEEE Trans. Syst. Man and Cybernet., vol. 23 (3), pp. 665-685.
9. Palm, R., 1992. Sliding mode fuzzy control, in Proc. of IEEE International Conference on Fuzzy Systems, pp.519-526.
10. Palm, R., D. Driankov, and H. Hellendoorn, 1996. Modelbased fuzzy control, Springer-Verlag, Berlin/New York/Heidelberg.
11. Palm, R. and C. Stutz, 2003. Generation of control sequences for a fuzzy gain scheduler, Int. J. of Fuzzy systems, vol. 5 (1), pp. 1-10.
12. Passino, K.M. and S. Yurkovich, 1998. Fuzzy control, Addison-Wesley Longman Inc..
13. Slotine, J.J.E. and W. Li, 1991. Applied nonlinear control, Prentice-Hall, Englewood Cliffs, NJ.
14. Takagi, T. and M. Sugeno, 1983. Derivation of fuzzy control rules from human operator's control actions, in Proc. of IFAC Symp. Fuzzy Inform., Knowledge Representation and Decision Analysis, pp. 55-60.
15. Takagi, T. and M. Sugeno, 1985. Fuzzy identification of systems and its applications to modeling and control, IEEE Transactions on Syst. Man and Cybern., vol. 15, pp.116-132.
16. Wang, L.-X., 1993. Stable adaptive fuzzy control of nonlinear systems, IEEE Trans. Fuzzy Syst., vol. 1 (1), pp. 146-155.

Paper Citation

in Harvard Style

Zhang J. and Böhme J. (2004). AN ADAPTIVE SLIDING-MODE FUZZY CONTROL (ASMFC) APPROACH FOR A CLASS OF NONLINEAR SYSTEMS . In Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 972-8865-12-0, pages 193-197. DOI: 10.5220/0001124801930197

in Bibtex Style

@conference{icinco04,
author={Jian-Hua Zhang and Johann F. Böhme},
title={AN ADAPTIVE SLIDING-MODE FUZZY CONTROL (ASMFC) APPROACH FOR A CLASS OF NONLINEAR SYSTEMS},
booktitle={Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2004},
pages={193-197},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001124801930197},
isbn={972-8865-12-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - AN ADAPTIVE SLIDING-MODE FUZZY CONTROL (ASMFC) APPROACH FOR A CLASS OF NONLINEAR SYSTEMS
SN - 972-8865-12-0
AU - Zhang J.
AU - Böhme J.
PY - 2004
SP - 193
EP - 197
DO - 10.5220/0001124801930197