Electrically induced joint movement control with iterative learning algorithm
This paper proposes to apply iterative learning control (ILC) method to achieve electrically induced joint movement as expected. In order to compensate the effects of external disturbances and muscle fatigue during electrical stimulation, an iterative learning control law is designed and a few simulation experiments are conducted based on a musculoskeletal dynamic model. The control performance is evaluated in comparison with the traditional PID control. The results indicate that the proposed iterative learning control can not only achieve better performance of the joint angle tracking than PID control, but also can initiatively adjust the stimulation level to compensate the deviations of joint movement resulting from the external disturbances and muscle fatigue.