Please use this identifier to cite or link to this item: http://rportal.lib.ntnu.edu.tw:80/handle/77345300/31961
Title: H-inf. tracking-based sliding mode control for uncertain nonlinear systems via an adaptive fuzzy-neural approach
Authors: 國立臺灣師範大學電機工程學系
W.-Y. Wang
M.-L. Chan
C.-C. James Hsu
T.-T. Lee
Issue Date: 1-Aug-2002
Publisher: IEEE Systems, Man, and Cybernetics Society
Abstract: A novel adaptive fuzzy-neural sliding-mode controller with H∞ tracking performance for uncertain nonlinear systems is proposed to attenuate the effects caused by unmodeled dynamics, disturbances and approximate errors. Because of the advantages of fuzzy-neural systems, which can uniformly approximate nonlinear continuous functions to arbitrary accuracy, adaptive fuzzy-neural control theory is then employed to derive the update laws for approximating the uncertain nonlinear functions of the dynamical system. Furthermore, the H∞ tracking design technique and the sliding-mode control method are incorporated into the adaptive fuzzy-neural control scheme so that the derived controller is robust with respect to unmodeled dynamics, disturbances and approximate errors. Compared with conventional methods, the proposed approach not only assures closed-loop stability, but also guarantees an H∞ tracking performance for the overall system based on a much relaxed assumption without prior knowledge on the upper bound of the lumped uncertainties. Simulation results have demonstrated that the effect of the lumped uncertainties on tracking error is efficiently attenuated, and chattering of the control input is significantly reduced by using the proposed approach
URI: http://rportal.lib.ntnu.edu.tw/handle/77345300/31961
ISSN: 1083-4419�
Other Identifiers: ntnulib_tp_E0604_01_039
Appears in Collections:教師著作

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.