ITERATIVE LEARNING CONTROL ST FUNCTIONAL NEUROMUSCULAR S

iterative learning controller (ILC) is proposed for the tracking control of functional neuromuscular stimulation (FNS) system performing the given task repeatedly. A P-type ILC updating law assisted by PD closed-loop con- troller is suggested for a simpler implementation. This kind of learning from repetitions control strategy supplies strong robustness in tracking control of uncertain time- varying FNS systems, which is essential for the adap- tation and customization of FNS applications. Nonlin- ear muscle recruitmcnt, linear muscle dynamics in force generation, and multiplicative nonlinear torque-angle and torquevelocity scaling factors are considered in the elec- trically stimulated muscle model for the simulation stud- ies. An one-segment planar system with passive con- straints on joint movement is taken as the skeletal model. Simulation results indicate that the control scheme of this paper ispromising for FNS system control.