Analysis of an Adaptive Fuzzy Control Scheme: Application to a Lower Limb Exoskeleton

Gait training helps in the assistance and rehabilitation of those who have problems with their locomotion system through better control of their limbs and also prevents degeneration of the musculoskeletal system. However, gait tracking should be accurate and the system should be robust for large-scale deployment. In this paper, an adaptive fuzzy control scheme (AFCS) is investigated for generating assisting torque for a lower limb exoskeleton consisting of knee-ankle orthosis. Grey wolf optimization is used for choosing optimum parameters of AFCS. Further, extensive simulation studies for trajectory tracking, parametric uncertainty handling and disturbance rejection analysis were carried out and a comprehensive comparative analysis was performed against a state-of-the-art control technique based on a coupled adaptive frequency oscillator (CAFO) to track a given non-sinusoidal pattern. Simulation results establish that the AFCS outperforms CAFO based control scheme for all cases.