Supervisory Model Predictive Impedance Control for Human Arm Movement

Supervisory Model Predictive Impedance Control for Human Arm Movement

Impedance control is described as the ability to modify characteristics of musculoskeletal impedance by the motor control system. This ability plays a significant role inposture control and fulfilling movements, in particular, at the presence of environmental disturbances. In addition, learning ability in human movement necessitates incorporating a type ofmodel for environment and/or musculoskeletal system. In this study a fuzzy supervisory controller unit is suggested tocoordinate impedance and model based control strategies. Results from computer simulations showed that both suitableimpedance values and a proper internal model are required to fulfill movements similar to those of humans under different circumstances. This study showed that beside this modulation,the maximum motor learning may occur in direction with the least impedance and the most kinematic error. It also concludedthat confronting abrupt changes in disturbance, the system managed to decrease error without learning the new dynamic sing previous knowledge by supervisory system. A part of this compensation is due to stiffness variations and another part is due to decreasing the influence of model based controller