The purpose of this paper is to make compliant training control of exoskeleton for ankle joint with electromyograph (EMG)-torque interface.
A virtual compliant mapping which is modeled by mass-spring-damper system is incorporated into the whole system at the reference input. The EMG-torque interface contains both data acquisition and torque estimator/predictor, and extreme learning machine is utilized for joint torque estimation/prediction from multiple channels of EMG signals.
The reference ankle joint angle to follow is produced from the compliance mapping whose input is the measured/predicted torque on healthy subjects. The control system works well with the desired angle to track. In the actuation level, the input torque to drive the ankle exoskeleton is less than the actual torque of the subject(s). This may have positive influence on diminishing overshoot of input torque from motors and protect the actuators. The torque prediction and final tracking control performance demonstrate the efficiency of the presented architecture.
This work can be beneficial to compliant training of ankle exoskeleton system for pilots and enhance current training control module in rehabilitation.
This work was supported by research project of University of Electronic Science and Technology of China under grant No. ZYGX2015KYQD044 and National Natural Science Foundation of China under grant No. 61603078.
Li, Z., Cheng, H., Guo, H. and Sun, X. (2017), "Compliant training control of ankle joint by exoskeleton with human EMG-torque interface", Assembly Automation, Vol. 37 No. 3, pp. 349-355. https://doi.org/10.1108/AA-12-2016-161
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