A disturbing recovery approach for lower extremity exoskeletons with passive ankle joints

This paper presents a disturbing recovery approach for lower extremity exoskeletons with passive ankle joints, which particularly works when an external disturbance is applied on the standing exoskeleton. Firstly, by analyzing the mechanical structure of lower extremity exoskeletons during its stance phase, the mathematical model is established using state-space equations. Then, on the basis of LQR (Linear Quadratic Regulator) theory, a novel neural network controller is designed to obtain the optimal solution for the balance control of model proposed. Finally, experimental results demonstrate that the proposed disturbing recovery approach not only has faster recovery speed, but also can achieve higher control precision than the traditional LQR.