An Adaptive Control for the Path Tracking of an Active Leg Prosthesis

Abstract

This paper presents an adaptive fuzzy-PID control strategy applied to an active lower limb prosthesis for trajectories tracking in normal walking, stairs climbing, and stairs descent. Trying to imitate a natural human limb, the prosthesis design challenges rehabilitating amputees to resume normal activities. A dynamic model of an ankle-knee active prosthesis is developed without ground reaction in a fiirst case and introduces ground effect in a second one to ameliorate prothesis performances. The obtained models are used to synthesize a control strategy based on TS fuzzy concepts and PID control to reproduce human lower limb behavior in a normal gait and climb and descent of stairs. The RSME errors are calculated to evaluate and compare the various results performances and eventually show the capacity of the proposed control with ground reaction impact on trajectory tracking. The RMSE values obtained for the four outputs of the fuzzy controller are very small for the different modes of locomotion. Moreover, they become weaker when the ground reaction forces are added to the model to show the role of these forces for the body equilibrium maintaining during the gait cycle. The developed approach ensured good trajectories tracking compared to a healthy leg even in presence of disturbances.