Neural Network-based Control of Neuromuscular Electrical Stimulation With Input Saturation

Abstract In this paper, we propose a new neural network-based controller for the lower leg limb motion tracking problem that is inherent to neuromuscular electrical stimulation systems. The control accounts for both parametric and functional uncertainties in the system and is capable of handling input saturation. The resulting control law guarantees practical tracking for the limb angular position. The control performance is demonstrated via a simulation.

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