Iterative learning control of functional neuromuscular stimulation systems

Abstract

A high-order Iterative Learning Control strategy is proposed for a better control of FNS system. Robust convergence properties have been investigated for both continuous-time and discrete-time high-order P-type ILC schemes. A suitable musculoskeletal model is utilized to conduct the simulation studies. Through extensive simulations, it is shown that the ILC method can give a better solution to the customization, adaptation and robustness problems in FNS system control. Moreover, it should be pointed out that unlike the conventional adaptive control method, the adaptation via ILC method is in a point-wise fashion. The ILC DCS is hopeful to be suitable for the real task execution both in the training stage use and in the daily-life use of the FNS systems.