Abstract
Recently various continuous adaptive fuzzy control schemes have been proposed to deal with nonlinear systems with poorly understood dynamics by using parameterized fuzzy approximators. However, practical applications call for discrete-time adaptive fuzzy controller design because almost all these controllers are implemented on digital computers. To meet such a demand, in this paper a discrete-time adaptive fuzzy control scheme is developed. The strategy ensures the global stability of the resulting closed-loop system in the sense that all signals involved are uniformly bounded and tracking error will be asymptotically in decay.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
I. J. Leontaritis and S. A. Billings, “Input-output parametric models for nonlinear systems. Part I and II,” International Journal of Control, vol. 41, pp. 303–344, 1985.
L.-X. Wang, “Stable adaptive fuzzy control of nonlinear system,” IEEE Trans, on Fuzzy Systems, vol. 1, pp. 146–155, 1993.
C.-Y. Su and Y. Stepanenko, “Adaptive control of a class of nonlinear systems with fuzzy logic,” IEEE Trans, on Fuzzy Systems, vol. 2, pp. 258–294, 1994.
Y.-G. Piao, H.-G. Zhang and Z. Bien, “Design of fuzzy direct controller and stability analysis for a class of nonlinear system,” Proceedings of the ACC, pp. 2274–2275, USA, 1998.
T. Chai and S. Tong, “Fuzzy direct adaptive control for a class of nonlinear systems,” Fuzzy Sets and Systems, vol. 103, no. 3, pp. 379–384, 1999.
H. Han, C.-Y. Su and S. Murakami, “Further results on adaptive control of a class of nonlinear systems with fuzzy logic,” Journal of Japan Society for Fuzzy Theory and System, vol. 11, no. 5, pp. 501–509, 1999.
S.-J. Wu and C.-T. Lin, “Global stability analysis of discrete time-invariant optimal fuzzy control systems,” International Journal of Fuzzy Systems, vol. 1, no. 1, pp. 60–68, 1999.
Katsuhisa Furuta, “VSS type self-tuning control,” IEEE Trans, on Industrial Electronics, vol. 40, no. 1, pp. 37–44, 1993.
F. Sun, Z. Sun, and P.-Y. Woo, “Stable neural-network-based adaptive control for sampled-data nonlinear systems,” IEEE Trans, on Neural Networks, vol. 9, no. 5, pp. 956–968, 1998.
S. Sastry and M. Bodson, Adaptive Control, Prentice Hall, 1989.
L.-X. Wang and J. M. Mendel, “Back-propagation fuzzy system as nonlinear dynamic system identifiers,” Proc. of IEEE Conf. on Fuzzy Systems, pp. 1409–1418, San Diego, 1992.
C.-J. Chien and L.-C. Fu, “Adaptive control of interconnected systems using neural network design,” Proc. of 37th IEEE Conf. on Decision and Control, Tampa, TL. 1998.
J.-J. Slotine and J. A. Coetsee, “Adaptive sliding controller synthesis for nonlinear systems,” Int. J Control, vol. 43, pp. 1631–1651, 1986.
Changyun Wen, “A robust adaptive controller with minimal modification for discrete time-varying systems,” IEEE Thins, on Auto. Control, vol. 39, no.5, pp. 987–991, 1994.
J.-J.E. Slotine and W. Li, Applied nonlinear control, Prentice Hall, 1991.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Han, H., Su, CY., Murakami, S. (2001). Fuzzy-Logic-Based Adaptive Control for a Class of Nonlinear Discrete-Time System. In: Ziarko, W., Yao, Y. (eds) Rough Sets and Current Trends in Computing. RSCTC 2000. Lecture Notes in Computer Science(), vol 2005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45554-X_29
Download citation
DOI: https://doi.org/10.1007/3-540-45554-X_29
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43074-2
Online ISBN: 978-3-540-45554-7
eBook Packages: Springer Book Archive