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    題名: RBF-network-based sliding mode control
    作者: Lin, Sinn-cheng;Chen, Yung-yaw
    貢獻者: 淡江大學資訊與圖書館學系
    日期: 1994-10
    上傳時間: 2011-05-20 09:51:16 (UTC+8)
    摘要: A sliding mode controller (SMC) design method based on radial basis function network (RBFN) is proposed in this paper. Similar to the multilayer perceptron, the RBFN also known to be a good universal approximator. In this work, the weights of the RBFN are changed according to some adaptive algorithms for the purpose of controlling the system state to hit a user-defined sliding surface and then slide along it. The initial weights of the RBFN can be set to small random numbers, and then online tuned automatically, no supervised learning procedures are needed. By applying the RBFN-based sliding mode controller to control a nonlinear unstable inverted pendulum system, the simulation results show the expected approximation sliding property was occurred, and the dynamic behavior of the control system can be determined by the sliding surface
    關聯: IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, TX , USA
    顯示於類別:[資訊與圖書館學系暨研究所] 會議論文

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