Predictor-Based Tracking For Neuromuscular Electrical Stimulation

Abstract

A new hybrid tracking controller for neuromuscular electrical stimulation is proposed. The control scheme uses sampled measurements and is designed by utilizing a numerical prediction of the state variables. The tracking error of the closed-loop system converges exponentially to zero and robustness to perturbations of the sampling schedule is exhibited. One of the novelties of our approach is the ability to satisfy a state constraint imposed by the physical system.