Abstract
This paper presents a novel robust fuzzy tracking control method for uncertain nonlinear systems. The Takagi-Sugeno fuzzy model is employed for fuzzy modeling of uncertain nonlinear system. Based on the fuzzy model, the internal model principle (IMP) is adopted to design the robust fuzzy tracking controller. Then the robust fuzzy observer is designed independently. Sufficient conditions are derived for stabilization of the robust fuzzy tracking controller and the robust fuzzy observer in the sense of Lyapunov asymptotic stability. The main contribution of this paper is the development of the robust fuzzy tracking control based on the internal model principle of uncertain nonlinear systems. A simulation example is given to illustrate the design procedures and asymptotic tracking performance of the proposed method.
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
Li, K., Thompson, S., Peng, J.: Modelling and prediction of NOx emission in a coal-fired power generation plant. Control Engineering Practice 12, 707–723 (2004)
Chiang, C.-L., Su, C.-T.: Tracking control of induction motor using fuzzy phase plane controller with improved genetic algorithm. Electric Power Systems Research 2, 239–247 (2005)
El, H.A., Bentalba, S.: Fuzzy path tracking control for automatic steering of vehicles. Robotics and Autonomous Systems 4, 203–213 (2003)
Marseguerra, M., Zio, E.: Model-free fuzzy tracking control of a nuclear reactor. Annals of Nuclear Energy 9, 953–981 (2003)
Park, C.-W., Cho, Y.-W.: Adaptive tracking control of flexible joint manipulator based on fuzzy model reference approach. IEE Proceedings: Control Theory and Applications 2, 198–204 (2003)
Tseng, C.-S., Chen, B.-S., Uang, H.-J.: Fuzzy tracking control design for nonlinear dynamic systems via T-S fuzzy model. IEEE Transactions on Fuzzy Systems 3, 381–392 (2001)
Kim, E.: Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic. IEEE Transactions on Fuzzy Systems 3, 368–378 (2004)
Tong, S.-C., Wang, T., Li, H.-X.: Fuzzy robust tracking control for uncertain nonlinear systems. International Journal of Approximate Reasoning 2, 73–90 (2002)
Guan, X., Chen, C.: Adaptive fuzzy control for chaotic systems with H infinity tracking performance. Fuzzy Sets and Systems 1, 81–93 (2003)
Yu, W.-S.: H infinity tracking-based adaptive fuzzy-neural control for MIMO uncertain robotic systems with time delays. Fuzzy Sets and Systems 3, 375–401 (2004)
Chang, Y.-C.: Robust tracking control for nonlinear MIMO systems via fuzzy approaches. Automatica 10, 1535–1545 (2000)
Ma, X.J., Sun, Z.Q., He, Y.Y.: Analysis and design of fuzzy controller and fuzzy observer. IEEE Transactions on Fuzzy Systems 1, 41–51 (1998)
Zhang, J., Fei, M.R.: Analysis and Design of Robust Fuzzy Controllers and Robust Fuzzy Observers of Uncertain Nonlinear Systems. In: The 6th World Congress on Intelligent Control and Automation, Dalian, China, pp. 3767–3771 (to appear, 2006)
Lee, H.J., Park, J.B., Chen, G.: Robust fuzzy control of nonlinear systems with parametric uncertainties. IEEE Transactions on Fuzzy Systems 2, 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
Zhang, J., Fei, M., Yang, T., Tan, Y. (2006). Robust Fuzzy Tracking Control of Nonlinear Systems with Uncertainty Via T-S Fuzzy Model. 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_21
Download citation
DOI: https://doi.org/10.1007/11881599_21
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)