| Title: | An Adaptive Friction Compensator Using Fourier Neural Networks |
| Other Titles: | 適應性傅立葉類神經網路之摩擦補償器設計 |
| Authors: | 楊哲豪
黃正自 |
| Contributors: | 工學院 |
| Keywords: | 適應性補償器；傅立葉類神經網路；摩擦力；adaptive compensator；Fourier neural network；friction |
| Date: | 2010-01-01 |
| Issue Date: | 2012-03-14 15:21:51 (UTC+8) |
| Abstract: | 針對伺服系統的摩擦補償問題，本論文提出一個以傅立葉級數類神經網路器的補償器設計。首先以一未知非線性函數模擬低速摩擦，接著藉由線性輸出的類神經網路重建此函數，以使適應性控制可以應用於此問題。然後建構一個強健適應性控制器，以達成追蹤動態錯誤實際穩定性。因為傅立葉級數係數可以事先被明確的計算出，因此可減輕線上計算量；此外，此設計也比現有的相似設計具有更快速的收斂速度。
A Fourier series neural network based friction compensator for a servo system with friction is proposed. The downward-bend low-velocity friction is modeled by an unknown nonlinear function, which is further resembled by the neural network with linear outputs to render the adaptive control applicable. Then a robust adaptive control approach is incorporated for achieving the practical tracking stability of the error dynamics. Since the Fourier series coefficients can be calculated explicitly and used in initializing the weights of the networks, therefore, it leads to faster convergence than existing similar designs. |
| Relation: | 華岡工程學報 ； 25期 (2010 / 01 / 01) ， P31 - 36 |
| Appears in Collections: | [College of Engineering] Chinese Culture University Hwa Kang Journal of Engineering
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