Adaptive Control with Concave/Convex Parameterization for an Electrically Stimulated Human Limb

In this paper, we propose a new adaptive controller for the lower leg limb motion tracking problem that is inherent to neuromuscular electrical stimulation systems. The control accounts for uncertainties in the system parameters by exploiting the concavity and convexity of the model functions. The resulting control law is continuous and guarantees practical tracking for the limb angular position and velocity. The control performance is demonstrated via a simulation.