Adaptive iteration learning control and its applications for FNS multi-joint motion

Functional neuromuscular stimulation (FNS) is one of new approaches in modern rehabilitation engineering. In this article, the adaptive iterative learning control algorithm is investigated for FNS multi-join limb motion system. At first, the FNS control system and its basic principles are given. Then, according to the nonlinear phenomena of the limb muscles, the discrete time-varying nonlinear model with undetermined and unexpected perturbations is defined, and a general expression based on the adaptive iteration learning control algorithm is developed, and the control algorithm structure block diagram is presented. Finally, based on multi-purpose FNS limb motion control system, the clinical experiments on motion trajectory-following of elbow flexion and wrist flexion were conducted by means of the adaptive iteration learning control algorithm and conventional control algorithm. The results of clinical studies have demonstrated that the adaptive iteration learning in control algorithm is more suitable for the improvement of the dynamic response characteristics and the stabilization of limb motion than conventional control algorithm. Furthermore, the stimulated patients have not any bad physiological reactions because the output electrical stimulation pulses generated by the adaptive iteration learning control algorithm vary gently