TY - GEN
T1 - MISO model free adaptive control of single joint rehabilitation robot driven by pneumatic artificial muscles
AU - Li, Yi
AU - Liu, Quan
AU - Meng, Wei
AU - Xie, Yuanlong
AU - Ai, Qingsong
AU - Xie, Sheng Q.
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/7
Y1 - 2020/7
N2 - Pneumatic artificial muscles (PAMs) are widely used as actuators in the field of rehabilitation robots, but their intrinsic compliance properties make it difficult to control precisely. In this paper, an improved multiple input single output model free adaptive control (MISO-IMFAC) method is proposed for the modeling the uncertainty, high nonlinearity and time-variability of the single joint rehabilitation robot driven by antagonistic PAMs, so as to realize the high-precision control of the joint angle. Considering the influence of the error change of adjacent time on the actual control effect, a new control law is formed by adding a term representing error change to the original control input criterion function. The experiment is carried out on a real rehabilitation robot and four types of errors are used to evaluate the effectiveness of the control system. The results show that the control algorithm can improve the accuracy of angle trajectory tracking at different amplitudes. Compared with original algorithm, the experiment errors of MISO-IMFAC were significantly reduced. In addition, the MISO-IMFAC still maintains stable performance in the process of load variation and external disturbance.
AB - Pneumatic artificial muscles (PAMs) are widely used as actuators in the field of rehabilitation robots, but their intrinsic compliance properties make it difficult to control precisely. In this paper, an improved multiple input single output model free adaptive control (MISO-IMFAC) method is proposed for the modeling the uncertainty, high nonlinearity and time-variability of the single joint rehabilitation robot driven by antagonistic PAMs, so as to realize the high-precision control of the joint angle. Considering the influence of the error change of adjacent time on the actual control effect, a new control law is formed by adding a term representing error change to the original control input criterion function. The experiment is carried out on a real rehabilitation robot and four types of errors are used to evaluate the effectiveness of the control system. The results show that the control algorithm can improve the accuracy of angle trajectory tracking at different amplitudes. Compared with original algorithm, the experiment errors of MISO-IMFAC were significantly reduced. In addition, the MISO-IMFAC still maintains stable performance in the process of load variation and external disturbance.
UR - https://www.scopus.com/pages/publications/85090389484
U2 - 10.1109/AIM43001.2020.9158805
DO - 10.1109/AIM43001.2020.9158805
M3 - 会议稿件
AN - SCOPUS:85090389484
T3 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
SP - 1700
EP - 1705
BT - 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2020
Y2 - 6 July 2020 through 9 July 2020
ER -