TY - JOUR
T1 - Myoelectric Model Reference Adaptive Control with Adaptive Kalman Filter for a soft elbow exoskeleton
AU - Toro-Ossaba, Alejandro
AU - Tejada, Juan C.
AU - Rúa, Santiago
AU - Núñez, Juan David
AU - Peña, Alejandro
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2024/1
Y1 - 2024/1
N2 - Rehabilitation and assistance exoskeletons have been widely studied because they allow to provide more effective, intensive, and adaptive therapies; in addition, they can be used to augment the user's capabilities in order to provide movement assistance. In particular, soft robotic exoskeletons have been researched during the past decade because they allow the device to adapt to the body contours, increasing the user's comfort. One of the main challenges in the development of soft robotic exoskeletons is the design of controllers that allow intuitive and active control of the device. This work addresses the development of a myoelectric Model Reference Adaptive Controller (MRAC) with an Adaptive Kalman Filter for controlling a cable driven soft elbow exoskeleton. The proposed MRAC controller proved to be suitable for both passive and active control of the soft elbow exoskeleton. The controlled system achieved a Mean Absolute Error (MAE) of approximately 4.5° in passive mode and 10° during active mode. Additionally, the active control mode allowed an average reduction of 34 % to 40 % in the joint torque RMS when performing dynamic Flexion–Extension movements. The active control mode is based on a surface electromyography (sEMG) joint torque estimation algorithm that achieved an approximate MAE of 1 N m. The proposed MRAC controller proved to be robust enough to adapt to the exoskeleton uncertainties and external disturbances; additionally, the adaptive scheme allowed the system to operate with only two sEMG channels and the measurement of the joint angle, which is estimated by using two Inertial Measurement Units.
AB - Rehabilitation and assistance exoskeletons have been widely studied because they allow to provide more effective, intensive, and adaptive therapies; in addition, they can be used to augment the user's capabilities in order to provide movement assistance. In particular, soft robotic exoskeletons have been researched during the past decade because they allow the device to adapt to the body contours, increasing the user's comfort. One of the main challenges in the development of soft robotic exoskeletons is the design of controllers that allow intuitive and active control of the device. This work addresses the development of a myoelectric Model Reference Adaptive Controller (MRAC) with an Adaptive Kalman Filter for controlling a cable driven soft elbow exoskeleton. The proposed MRAC controller proved to be suitable for both passive and active control of the soft elbow exoskeleton. The controlled system achieved a Mean Absolute Error (MAE) of approximately 4.5° in passive mode and 10° during active mode. Additionally, the active control mode allowed an average reduction of 34 % to 40 % in the joint torque RMS when performing dynamic Flexion–Extension movements. The active control mode is based on a surface electromyography (sEMG) joint torque estimation algorithm that achieved an approximate MAE of 1 N m. The proposed MRAC controller proved to be robust enough to adapt to the exoskeleton uncertainties and external disturbances; additionally, the adaptive scheme allowed the system to operate with only two sEMG channels and the measurement of the joint angle, which is estimated by using two Inertial Measurement Units.
KW - Adaptive Kalman Filter
KW - Elbow exoskeleton
KW - Model Reference Adaptive Control (MRAC)
KW - Myoelectric (EMG) control
KW - Soft robotics
UR - http://www.scopus.com/inward/record.url?scp=85175534643&partnerID=8YFLogxK
U2 - 10.1016/j.conengprac.2023.105774
DO - 10.1016/j.conengprac.2023.105774
M3 - Artículo
AN - SCOPUS:85175534643
SN - 0967-0661
VL - 142
JO - Control Engineering Practice
JF - Control Engineering Practice
M1 - 105774
ER -