會議論文
| 學年 | 83 |
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| 學期 | 1 |
| 發表日期 | 1994-10-01 |
| 作品名稱 | RBF-network-based sliding mode control |
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| 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 | en |
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| 出處 | IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, TX , USA |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/53603 ) |