Integration of an Empirical Mode Decomposition Algorithm With Iterative Learning Control for High-Precision Machining

2013 ◽  
Vol 18 (3) ◽  
pp. 878-886 ◽  
Author(s):  
Meng-Shiun Tsai ◽  
Chung-Liang Yen ◽  
Hong-Tzong Yau
Author(s):  
J. H. Wu ◽  
H Ding

This paper studies the repetitive motion control of a high-acceleration and high-precision platform driven by linear motors. The control scheme comprises an anticipatory iterative learning control (A-ILC) component and a cascaded control structure including an inner-loop velocity PI controller and an outer-loop position P controller. During the motion process, the cascaded controller remains invariant while the A-ILC adjusts the reference command cycle by cycle to achieve better performance. Experiments are carried out to validate the proposed control structure. The results confirm that the proposed control scheme can improve the system performance significantly in both low-speed trajectory tracking motions and fast point-to-point motion. In the experiments, P-type and D-type ILCs are also utilized to adjust the reference command. Compared with the A type, P-type ILC leads to larger tracking error bounds and D-type ILC lacks a fast convergence rate for low-speed motions, while for fast point-to-point motion these two types of ILC are unable to work well.


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