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標題RBF-network-based sliding mode control

學年83

學期1

發表日期1994-10-01

作品名稱RBF-network-based sliding mode control

作品名稱（其他語言）

著者Lin, Sinn-cheng; Chen, Yung-yaw

作品所屬單位淡江大學資訊與圖書館學系

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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

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語言英文

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國別

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出處IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, TX , USA

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