Abstract
Adaptive dynamic surface fuzzy control approach is proposed for a class of uncertain nonlinear systems in strict-feedback form. The dynamic surface control technique is introduced to overcome the problem of explosion of terms associated with backstepping design method. Fuzzy logic system is used as a universal approximator to approximate unstructured uncertain functions and the bounds of the reconstruction error is estimated online. The algorithm has the adaptive mechanism with minimum learning parameterizations. Furthermore, all the signals in the closed-loop systems are guaranteed to be semi-globally uniformly ultimately bounded and the output of the system is proved to converge to a small neighborhood of the desired trajectory. The control performance can be guaranteed by an appropriate choice of the design parameters. Simulation results demonstrate the effectiveness of the proposed control method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Kokotovic, P.V.: The Joy of Feedback. IEEE Contr. Syst. Mag. 3, 7–17 (1992)
Swaroop, D., Gerdes, C., Yip, P.P., Herdrick, J.K.: Dynamic Surface Control for a Class of Nonlinear Systems. IEEE Trans. Autom. Control. 45, 1893–1899 (2000)
Wang, D., Huang, J.: Neural Network-Based Adaptive Dynamic Surface Control for a Class of Uncertain Nonlinear Systems in Strict-Feedback Form. IEEE Trans. Neural Networks 16, 195–202 (2005)
Wang, L.X.: Adaptive Fuzzy Systems and Control: Design and Stability Analysis. Prentice-Hall, Englewood Cliffs (1994)
Chen, G., Wang, S., Zhang, J.: Robust and Adaptive Backstepping Control for Nonlinear Systems Using Fuzzy Logic Systems. In: Wang, L., Jin, Y. (eds.) FSKD 2005. LNCS (LNAI), vol. 3614, pp. 452–461. Springer, Heidelberg (2005)
Chen, G., Wang, S.: Robust Control of Time-Varying Nonlinear Systems with Unknown Control Directions. Control and Decision 20, 1397–1400 (2005)
Yang, Y., Feng, G., Ren, J.: A Combined Backstepping and Small-Gain Approach to Robust Adaptive Fuzzy Control for Strict-Feedback Nonlinear Systems. IEEE Trans. Syst. Man, Cybern. 34, 406–420 (2004)
Chen, G., Wang, S., Zhang, J.: Robust Adaptive Fuzzy Control for Uncertain Nonlinear Systems. In: Wang, L., Jin, Y. (eds.) FSKD 2005. LNCS (LNAI), vol. 3613, pp. 841–850. Springer, Heidelberg (2005)
Jagannathan, S., Lewis, F.L.: Robust Backstepping Control of a Class of Nonlinear Systems Using Fuzzy Logic. Inform. Sci. 123, 223–240 (2000)
Chen, G., Wang, S.: Robust Control For Multi-fingered Hand Manipulation in a Constrained Environment. Acta Automatica Sinica 31, 901–906 (2005)
Chen, G., Wang, S.: Dynamic Control of Four-Fingered Hand Manipulation with Sliding. Proceedings of the World Congress on Intelligent Control and Automation 6, 4855–4859 (2004)
Chen, G., Wang, S., Zhang, J.: Adaptive Neural Network Control for Multi-fingered Robot Hand Manipulation in the Constrained Environment. In: Wang, L., Chen, K., S. Ong, Y. (eds.) ICNC 2005. LNCS, vol. 3611, pp. 270–273. Springer, Heidelberg (2005)
Zheng, F., Wang, Q.G., Lee, T.H.: Adaptive and Robust Controller Design for Uncertain Nonlinear Systems via Fuzzy Modeling Approach. IEEE Trans. Syst. Man, Cybern. 34, 166–178 (2004)
Lee, H.J., Park, J.B., Chen, G.: Robust Fuzzy Control of Nonlinear Systems with Parameter Uncertainties. IEEE Trans. Fuzzy Syst. 9, 369–379 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gang, C. (2006). Adaptive Dynamic Surface Fuzzy Control for a Class of Uncertain Nonlinear Systems. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_22
Download citation
DOI: https://doi.org/10.1007/11881599_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45916-3
Online ISBN: 978-3-540-45917-0
eBook Packages: Computer ScienceComputer Science (R0)