標題: H-infinity tracking-based sliding mode control for uncertain nonlinear systems via an adaptive fuzzy-neural approach
作者: Wang, WY
Chan, ML
Hsu, CCJ
Lee, TT
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: adaptive control;fuzzy-neural approximator;H-infinity tracking performance;sliding mode control;uncertain nonlinear systems
公開日期: 1-Aug-2002
摘要: In this paper, a novel adaptive fuzzy-neural sliding mode controller with H-infinity 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-infinity 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-infinity 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://dx.doi.org/10.1109/TSMCB.2002.1018767
http://hdl.handle.net/11536/28613
ISSN: 1083-4419
DOI: 10.1109/TSMCB.2002.1018767
期刊: IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
Volume: 32
Issue: 4
起始頁: 483
結束頁: 492
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