TY - GEN
T1 - Dynamics Compensation Strategy for Control of Lower Extremity Exoskeleton
AU - Pei, Pei
AU - Pei, Zhongcai
AU - Gu, Han
AU - Tang, Zhiyong
AU - Chen, Weihai
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - Lower extremity exoskeleton is an intelligent system used in the military and medical rehabilitation field. Its control methods can be divided into model-based control method and model-free control method. In model-based control method, it is required to design the control rates based on the exoskeleton dynamics characteristic to maintain good dynamics. However, the dynamic model of exoskeleton is a complex non-linear system with multi-inputs and multi-outputs. It is difficult to obtain a precise model describing the dynamic characteristics. In addition, a precise exoskeleton dynamics model will increase the computational complexity. In this paper, the dynamic model of the lower extremity exoskeleton is established based on Lagrange method, and the unknown parameters in the dynamic model are identified by the Least-Square Method to obtain a more accurate system dynamics model. Then, the output results are used as the dynamic compensation of the force control inner loop in robot driving joint. The simulation results show the dynamic compensation algorithm can improve the tracking accuracy and dynamic performance of robot control.
AB - Lower extremity exoskeleton is an intelligent system used in the military and medical rehabilitation field. Its control methods can be divided into model-based control method and model-free control method. In model-based control method, it is required to design the control rates based on the exoskeleton dynamics characteristic to maintain good dynamics. However, the dynamic model of exoskeleton is a complex non-linear system with multi-inputs and multi-outputs. It is difficult to obtain a precise model describing the dynamic characteristics. In addition, a precise exoskeleton dynamics model will increase the computational complexity. In this paper, the dynamic model of the lower extremity exoskeleton is established based on Lagrange method, and the unknown parameters in the dynamic model are identified by the Least-Square Method to obtain a more accurate system dynamics model. Then, the output results are used as the dynamic compensation of the force control inner loop in robot driving joint. The simulation results show the dynamic compensation algorithm can improve the tracking accuracy and dynamic performance of robot control.
KW - Dynamical model
KW - Dynamics compensation strategy
KW - Lower extremity exoskeleton
KW - Parameter identification
UR - https://www.scopus.com/pages/publications/85085858266
U2 - 10.1109/CIS-RAM47153.2019.9095842
DO - 10.1109/CIS-RAM47153.2019.9095842
M3 - 会议稿件
AN - SCOPUS:85085858266
T3 - Proceedings of the IEEE 2019 9th International Conference on Cybernetics and Intelligent Systems and Robotics, Automation and Mechatronics, CIS and RAM 2019
SP - 1
EP - 6
BT - Proceedings of the IEEE 2019 9th International Conference on Cybernetics and Intelligent Systems and Robotics, Automation and Mechatronics, CIS and RAM 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE International Conference on Cybernetics and Intelligent Systems and Robotics, Automation and Mechatronics, CIS and RAM 2019
Y2 - 18 November 2019 through 20 November 2019
ER -