Abstract
Rehabilitation robots play an important role in the rehabilitation field, and effective human-robot interaction contributes to promoting the development of the rehabilitation robots. Though many studies about the human-robot interaction have been carried out, there are still several limitations in the flexibility and stability of the control system. Therefore, we proposed an advanced adaptive control method for lower limb rehabilitation robot. The method was devised with a dual closed loop control strategy based on the surface electromyography (sEMG) and plantar pressure to improve the robustness of the adaptive control for the rehabilitation robots. First, in the outer loop control, an advanced variable impedance controller based on the sEMG and plantar pressure was designed to correct robot's reference trajectory. Then, in the inner loop control, a sliding mode iterative learning controller (SMILC) based on the variable boundary saturation function was designed to achieve the tracking of the reference trajectory. The experiment results showed that, in the designed dual closed loop control strategy, a variable impedance controller can effectively reduce trajectory tracking errors and adaptively modify the reference trajectory synchronizing with the motion intention of patients; the designed sliding mode iterative learning controller can effectively reduce chattering in sliding mode control and excellently achieve the tracking of rehabilitation robot's reference trajectory. This study can improve the performance of the human-robot interaction of the rehabilitation robot system, and expand the application to the rehabilitation field.
Highlights
The rehabilitation robots have shown great advantages and have attracted more attention in rehabilitation field, which can assist patients in rehabilitation training and effectively alleviate the work pressure of the therapist (Lo et al, 2010)
We proposed an advanced adaptive control method for lower limb rehabilitation robot, which was designed with a dual closed loop control strategy based on the surface electromyography (sEMG) and plantar pressure
In order to verify the effectiveness of the proposed method, the horizontal extension and flexion movement of the lower limb was chosen as the experimental paradigm
Summary
The rehabilitation robots have shown great advantages and have attracted more attention in rehabilitation field, which can assist patients in rehabilitation training and effectively alleviate the work pressure of the therapist (Lo et al, 2010). The variable impedance controller was designed with impedance coefficients corrected in real-time by the lower limb sEMG activity and muscle contribution rate, which can realize the adaptive adjustment of reference trajectory of the robot according to human stiffness and damping. The desired rehabilitation robot trajectory was corrected by the lower limb sEMG and human-robot interaction force, and the reference trajectory was obtained synchronizing with patient’s motion intention and ability. The variable impedance control model, established based on human lower limb sEMG, can adaptively adjust the impedance parameter according to the changes of lower limb activity, and correct the desired trajectory of the rehabilitation robot and generate a reference trajectory, which is in greater agreement with patients’ motion ability. By sensing the human-robot interaction force and suppressing periodic and non-periodic disturbances, we can quickly complete the tracking of reference trajectory and improve system control robustness, realizing adaptive compliance control of the humanrobot system
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