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.