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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/103412


    Title: Intelligent nonsingular terminal sliding-mode control via perturbed fuzzy neural network
    Authors: Chun-Fei Hsu, Tsu-Tian Lee, and Kazuo Tanaka
    Keywords: Intelligent control;Sliding-mode control;Fuzzy neural network;Perturbed membership function.
    Date: 2014
    Issue Date: 2015-07-21 12:08:44 (UTC+8)
    Abstract: In this paper, an intelligent nonsingular terminal sliding-mode control (INTSMC)
    system, which is composed of a terminal neural controller and a robust compensator, is proposed for an unknown nonlinear system. The terminal neural controller including a
    perturbed fuzzy neural network (PFNN) is the main controller and the robust compensator is
    designed to eliminate the effect of the approximation error introduced by the PFNN upon the system stability. The PFNN is used to approximate an unknown nonlinear term of the system dynamics and perturbed asymmetric membership functions are used to handle rule
    uncertainties when it is hard to exactly determine the grade of membership functions. In additional, Lyapunov stability theory is used to discuss the parameter learning and system stability of the INTSMC system. Finally, the proposed INTSMC system is applied to an inverted pendulum and a voice coil motor actuator. The simulation and experimental results show that the proposed INTSMC system can achieve favorable tracking performance and is robust against parameter variations in the plant.
    Relation: International Scientific Journal Engineering Applications of Artificial Intelligence
    Appears in Collections:[電機工程學系暨研究所] 期刊論文

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