Adaptive fuzzy tracking control of a human lower limb with an exoskeleton

In this paper, the objective is to develop a lower limb exoskeleton to produce a knee position trajectory that will enable a human shank to track any continuous desired trajectory (or constant setpoint). Given a desired trajectory of knee position, Lyapunov-based adaptive fuzzy control is developed to control the human quadriceps femoris muscle undergoing nonisometric contractions. The developed controller through the use of an integral Lyapunov function does not require a muscle model and can be proven to yield asymptotic stability for a nonlinear muscle model and an exoskeleton model in the presence of bounded nonlinear disturbances (e.g., spasticity, fatigue). The controller singularity problem is elegantly solved as it avoids the nonlinear parametrization from entering into the adaptive control and learning control. The performance of the controller is demonstrated through closed-loop experiments on human subjects. The experiments illustrate the ability of the exoskeleton to enable the leg shank to track single and multiple period trajectories with different periods and ranges of motion.