The Feedforward Friction Compensation of Motion System Using Genetic Algorithms
碩士 === 國立臺北科技大學 === 自動化科技研究所 === 93 === The need for high speed and high precision motion control in the machine tool industry and in the manufacture of semiconductors is rapidly growing. In order to achieve the performance, friction effects have to be considered in the motion system. Friction can...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2005
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| Online Access: | http://ndltd.ncl.edu.tw/handle/8e5z8q |
| Summary: | 碩士 === 國立臺北科技大學 === 自動化科技研究所 === 93 === The need for high speed and high precision motion control in the machine tool industry and in the manufacture of semiconductors is rapidly growing. In order to achieve the performance, friction effects have to be considered in the motion system. Friction can lead to tracking errors, limit cycles and undesired stick-slip motion.
This paper proposes a feedforward friction compensator based on LuGre friction model. The key parameters in this model are firstly estimated by experiment of parameter identification and then optimized by genetic learning algorithm. When compared with the conventional black box learning algorithm, this mode-based compensator uses only five parameters to model the linear friction and the corresponding convergent rate of parameters is fast in the learning process.
Finally, the friction compensated performance of proposed algorithm is evaluated and compared with the traditional uncompensated system. The simulated and experimented results show that the velocity error is drastically improved by the feedforward friction compensator in a motion system.
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