教師著作

Permanent URI for this collectionhttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/31268

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Author: search.filters.author.M.-L. ChanSubject: search.filters.subject.Adaptive fuzzy control

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    Robust control of the mismatched systems with the fuzzy integral sliding controller
    (2003-10-08) C.-W. Tao; M.-L. Chan; W.-Y. Wang
    An adaptive fuzzy integral sliding mode controller for mismatched time-varying linear systems is presented in this paper. The proposed fuzzy integral sliding mode controller is designed to have zero steady state system error under step inputs and alleviate the undesired chattering around the sliding surface. The parameters in the fuzzy mechanism are adapted on-line to improve the performance of the fuzzy integral sliding mode control system. Thus, the bounds of the uncertainties are not required to be known in advance. The designed fuzzy integral sliding mode control system is shown to be invariant on the sliding surface. Moreover, the reaching mode of the sliding surface is guaranteed and the close-loop system is stable. Simulation results are included to illustrate the effectiveness of the presented fuzzy integral sliding mode controller.
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    Adaptive fuzzy control for strict-feedback canonical nonlinear systems with H-inf. tracking performance
    (IEEE Systems, Man, and Cybernetics Society, 2000-12-01) W.-Y. Wang; M.-L. Chan; T.-T. Lee; C.-H. Liu
    In this paper, an adaptive fuzzy controller for strict-feedback canonical nonlinear systems is proposed. The completely unknown nonlinearities and disturbances of the systems are considered. Since fuzzy logic systems can uniformly approximate nonlinear continuous functions to arbitrary accuracy, the adaptive fuzzy control theory is employed to derive the control law for the strict-feedback system with unknown nonlinear functions and disturbances. Moreover, H∞ tracking performance is applied to substantially attenuate the effect of the modeling errors and disturbances. Finally, examples are simulated to confirm the applicability of the proposed methods.