Find in Library
Search millions of books, articles, and more
Indexed Open Access Databases
Iterative Learning with Adaptive Sliding Mode Control for Trajectory Tracking of Fast Tool Servo Systems
oleh: Xiuying Xu, Pengbo Liu, Shuaishuai Lu, Fei Wang, Jingfang Yang, Guangchun Xiao
Format: | Article |
---|---|
Diterbitkan: | MDPI AG 2024-04-01 |
Deskripsi
To address the tracking control problem of the periodic motion fast tool servo system (FTS), we propose a control method that combines adaptive sliding mode control with closed-loop iterative learning control. Adaptive sliding mode control enhances the system’s robustness to external non-repetitive disturbances, and exponential gain iterative learning control compensates for the influence of periodic disturbances such as cutting force. The experimental results show that the proposed iterative learning controller based on adaptive sliding mode control can effectively eliminate the influence of various interference factors, achieve accurate tracking of the FTS system’s motion trajectory within a limited number of iterations, and ensure the stability of the system, which has the advantages of a fast convergence speed, high tracking accuracy, and strong robustness.