H-inf. tracking-based sliding mode control for uncertain nonlinear systems via an adaptive fuzzy-neural approach

dc.contributor 國立臺灣師範大學電機工程學系 zh_tw
dc.contributor.author W.-Y. Wang en_US
dc.contributor.author M.-L. Chan en_US
dc.contributor.author C.-C. James Hsu en_US
dc.contributor.author T.-T. Lee en_US
dc.date.accessioned 2014-10-30T09:28:16Z
dc.date.available 2014-10-30T09:28:16Z
dc.date.issued 2002-08-01 zh_TW
dc.description.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 en_US
dc.description.uri http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1018767 zh_TW
dc.identifier ntnulib_tp_E0604_01_039 zh_TW
dc.identifier.issn 1083-4419� zh_TW
dc.identifier.uri http://rportal.lib.ntnu.edu.tw/handle/20.500.12235/31961
dc.language en zh_TW
dc.publisher IEEE Systems, Man, and Cybernetics Society en_US
dc.relation IEEE Transactions on Systems, Man, And Cybernetics-Part B, 32(4), 483-492. en_US
dc.subject.other Adaptive control en_US
dc.subject.other fuzzy-neural approximator en_US
dc.subject.other tracking performance en_US
dc.subject.other sliding mode control en_US
dc.subject.other uncertain nonlinear systems en_US
dc.title H-inf. tracking-based sliding mode control for uncertain nonlinear systems via an adaptive fuzzy-neural approach en_US
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