Observer-based direct adaptive fuzzy control of uncertain nonlinear systems and its applications
- 223 Downloads
A direct adaptive fuzzy control algorithm is developed for a class of uncertain SISO nonlinear systems. In this algorithm, it doesn’t require to assume that the system states are measurable. Therefore, it is needed to design an observer to estimate the system states. Compared with the numerous alternative approaches with respect to the observer design, the main advantage of the developed algorithm is that on-line computation burden is alleviated. It is proven that the developed algorithm can guarantee that all the signals in the closed-loop system are uniformly ultimately bounded and the tracking error converges to a small neighborhood around zero. The simulation examples validate the feasibility of the developed algorithm.
KeywordsAdaptive fuzzy control nonlinear systems uncertainties
Unable to display preview. Download preview PDF.
- D. Huang, “Adaptive feedback control algorithm,” Physical Review E, vol. 73, 066204, 2006.Google Scholar
- L. X. Wang, “Fuzzy systems are universal approximators,” Proc. of IEEE International Conference on Fuzzy Systems, San Diego, 1992: 1163–1170.Google Scholar
- N. Essounbouli and A. Hamzaoui, “Direct and indirect robust adaptive fuzzy controllers for a class of nonlinear systems,” International Journal of Control, Automation, and Systems, vol. 4, no. 2, pp. 146–154, 2006.Google Scholar
- P. A. Phan and T. J. Gale, “Direct adaptive fuzzy control with less restrictions on the control gain,” International Journal of Control, Automation, and Systems, vol. 5, no. 6, pp. 621–629, 2007.Google Scholar
- Q. Zhang and B. Delyon, “A new approach to adaptive observer design for MIMO systems,” Proc. of American Control Conference, pp. 1545–1550, 2001.Google Scholar
- Q. Zhang, “Revisiting different adaptive observers through a unified formulation,” Proc. of IEEE Conference on Decision and Control, pp. 3067–3072, 2005.Google Scholar
- X. J. Wei and Y. W. Jing, “Robust adaptive fuzzy controller for nonlinear systems based on approximation errors,” Proc. of American Control Conference, Boston, Massachusetts, pp. 459–463, 2004.Google Scholar
- C. T. Chen, Linear System Theory and Design, 3rd ed., Oxford Univ. Press, London, U.K. 1999.Google Scholar