CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
An iterative learning controller for a cable-driven hand rehabilitation robot
Siyuan Liu;  Deyuan Meng;  Long Cheng;  Miao Chen
2017
Conference NameIECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
Conference Date29 Oct.-1 Nov. 2017
Conference PlaceBeijing
CountryChina
AbstractRobots 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.
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23121
Collection复杂系统管理与控制国家重点实验室_先进机器人
Recommended Citation
GB/T 7714
Siyuan Liu, Deyuan Meng, Long Cheng,et al. An iterative learning controller for a cable-driven hand rehabilitation robot[C],2017.
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