TY - GEN
T1 - An iterative learning controller for a cable-driven hand rehabilitation robot
AU - Liu, Siyuan
AU - Meng, Deyuan
AU - Cheng, Long
AU - Chen, Miao
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/15
Y1 - 2017/12/15
N2 - Robots are widely used to help post-stoke patients conduct rehabilitation training for the motor function recovery. Because of the existence of repetitiveness in the rehabilitation training, a high-order iterative learning controller (ILC) is proposed for one hand rehabilitation robot in this paper. A series of tracking experiments are conducted to verify the effectiveness and superiority of the proposed controller by comparing to the PID controller, the P-type ILC, and the PD-type ILC. Experimental results show that: (1) the average tracking errors of the P-type ILC and the PD-type ILC are smaller than that of the PID controller, and the steady-state performance of the PD-type ILC is better than that of the P-type ILC; and (2) compared to the PD-type ILC, the average transient performance index of the high-order ILC is decreased by 33.9%. The mean value and variance of the tracking error are decreased by 21.1% and 14.4%, respectively.
AB - Robots are widely used to help post-stoke patients conduct rehabilitation training for the motor function recovery. Because of the existence of repetitiveness in the rehabilitation training, a high-order iterative learning controller (ILC) is proposed for one hand rehabilitation robot in this paper. A series of tracking experiments are conducted to verify the effectiveness and superiority of the proposed controller by comparing to the PID controller, the P-type ILC, and the PD-type ILC. Experimental results show that: (1) the average tracking errors of the P-type ILC and the PD-type ILC are smaller than that of the PID controller, and the steady-state performance of the PD-type ILC is better than that of the P-type ILC; and (2) compared to the PD-type ILC, the average transient performance index of the high-order ILC is decreased by 33.9%. The mean value and variance of the tracking error are decreased by 21.1% and 14.4%, respectively.
KW - Iterative learning control (ILC)
KW - P-type ILC
KW - PD-type ILC
KW - hand rehabilitation robot
UR - https://www.scopus.com/pages/publications/85046654872
U2 - 10.1109/IECON.2017.8216989
DO - 10.1109/IECON.2017.8216989
M3 - 会议稿件
AN - SCOPUS:85046654872
T3 - Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
SP - 5701
EP - 5706
BT - Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017
Y2 - 29 October 2017 through 1 November 2017
ER -