Hierarchical Neuro-Fuzzy Control for Micropositioning Systems Using Flexural Bearings
碩士 === 國立中興大學 === 機械工程學系 === 88 === Abstract The micropositioning system using flexural bearings (e. g., for wafer steppers and coarse-fine positioning systems) is a system of infinite degrees of freedom. It is difficult to design the controller for the partial differential equ...
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Format: | Others |
Language: | zh-TW |
Published: |
2000
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Online Access: | http://ndltd.ncl.edu.tw/handle/40968926371945341170 |
Summary: | 碩士 === 國立中興大學 === 機械工程學系 === 88 === Abstract
The micropositioning system using flexural bearings (e. g., for wafer steppers and coarse-fine positioning systems) is a system of infinite degrees of freedom. It is difficult to design the controller for the partial differential equation of the system directly. In this thesis, we use the closed-form dynamics model proposed in [1] for the design of micropositioning controller. We propose a hierarchical fuzzy control using neural network backpropagation training algorithm for the micropositioning system. Simulation results show that the suggested control strategy can actively suppress the flexible vibration and have good performance in micropositioning. Comparison with the result of LQR control is also presented.
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