頁籤選單縮合
題 名 | Robust Neural Network Control of Rigid Link Flexible-Joint Robots |
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作 者 | Kwan,C. M.; Lewis,F. L.; Kim,Y. H.; | 書刊名 | Asian Journal of Control |
卷 期 | 1:3 1999.09[民88.09] |
頁 次 | 頁188-197 |
分類號 | 448.94 |
關鍵詞 | Flexible-joint robot; Neural networks; Robust control; |
語 文 | 英文(English) |
英文摘要 | A robust Neural Network (NN) controller is proposed for the motion control of rigid-link flexible-joint (RLFJ) robots. No weak joint elasticity assumption is needed. The NNs are used to approximate three very complicated nonlinear functions. Our NN approach requires no off-line learning phase, and no lengthy and tedious preliminary analysis to find the regression matrices. Most importantly, we can guarantee the uniformly ultimately bounded (UUB) stability of tracking errors and NN weights. The controller can be regarded as a universal reusable controller because the same controller can be directly applied to different RLFJ robots with different masses and lengths within the same class, for instance, of two-link revolute RLFJ robots. |
本系統中英文摘要資訊取自各篇刊載內容。