Name
Abstract | ||
|---|---|---|
Active rehabilitation training can improve patients' neural engagement and the rehabilitation effects. A position based impedance control strategy is proposed for implement of active training in this paper. Firstly, it is necessary to accurately estimate patients' active torques during the training process, which can be calculated by using the human-robot dynamic model. A novel friction model is designed, where the influence of the joint coupling factor and viscosity is considered to improve the model accuracy. In order to prevent sudden changes of the interaction force, a virtual tunnel around the reference trajectory is established to limit the motion range to ensure patient safety in case of emergency, such as muscle spasm. Then, a position based impedance control strategy designed in the joint space is used to convert human torques into the required movement. The strategy is implemented by a double closed loop control structure, the outer loop of which converts the interaction force into angular, angular velocity, and angular acceleration deviations by the inverse impedance equation. The regulated trajectory will be used as reference for the inner position control loop. The experimental results show that the proposed system dynamic model can be used to accurately estimate the patients' active torques, and the proposed control strategy can be used to design a compliant human-robot interaction interface, so that patients can complete the training task comfortably and naturally, and also safety of the training can be ensured. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/EMBC.2019.8857186 | 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) |
Field | DocType | Volume |
Coupling,Torque,Angular velocity,Control theory,Computer science,Electronic engineering,Angular acceleration,Impedance control,Control system,Robot,Trajectory | Conference | 2019 |
ISSN | Citations | PageRank |
1557-170X | 0 | 0.34 |
References | Authors | |
0 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xu Liang | 1 | 1 | 0.72 |
| Weiqun Wang | 2 | 25 | 12.73 |
| Zeng-Guang Hou | 3 | 2293 | 167.18 |
| Shixin Ren | 4 | 0 | 3.38 |
| Jiaxing Wang | 5 | 0 | 0.34 |
| Weiguo Shi | 6 | 0 | 2.03 |
| Liang Peng | 7 | 26 | 12.81 |
| Tingting Su | 8 | 0 | 1.35 |