Development of Robust Iterative Learning Control Algorithm for Compensation of Friction and Tracking Error

• Main Authors: Yung-Che Jian, 簡永哲
• Other Authors: Meng-Shiun Tsai
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/21636448554619012537

碩士 === 國立中正大學 === 機械系 === 90 === One of the major error sources for machining errors is the friction existing in the contact layer. In order to achieve high precision machinery, friction compensation could be very important. In this paper, the friction effects on the system dynamics are analyzed using the Bristle model. The describing function method is utilized to analyze the stability of the servo system. A novel command-based iterative learning architecture is proposed for the compensation of the plant uncertainties and its friction behavior. The methodology is to update the input-command based on the error from the previous machinery process. It is shown that the ILC controller results in a concave command in the changing quadrant for tracking a circle such that the quadrant protrusions caused by the friction can be reduced. To further enhance the performance of the P-type ILC, a robust ILC controller is utilized to include the system uncertainties into the design process and the better performance are shown in the simulation. Finally, experiment results show that the proposed design method can reduce the tracking errors significantly.