A framework for sensorless torque estimation and control in wearable exoskeletons

This paper is aimed at describing a framework to implement sensorless torque estimation and control in wearable exoskeletons, for the purpose of handling power augmentation tasks. The proposed method relies on accurately identifying and compensating the joint-level disturbance torques caused by stiction, viscous friction, and gravitational loads. Utilizing off-the-shelf techniques, the characteristics of these disturbances are primarily identified. Subsequently, additional torque inputs are superimposed to the system via feedforward loops in a way to counteract to these disturbances. Having compensated frictional and gravitational loads acting on the actuation module; we are able to estimate the external torque exerted at each joint by using disturbance observers. In this manner, torque control is enabled without any requirement of built-in torque sensing units. In order to validate the proposed framework, we conducted weight lifting and upholding experiments on able-bodied human subjects with and without wearing the upper extremity of exoskeleton suit. Comparison of EMG and IEMG signals acquired in two cases indicates that the exoskeleton system provides sufficient power augmentation reliably. In conclusion, the proposed method is validated to be efficient and it can be potentially used for rehabilitation, training and power augmentation tasks.