基于自适应迭代学习算法的FNS肢体运动控制

FNS Limb Motion Control Based on Adaptive Iterative Learning Control Algorithm

首先介绍 FNS系统的构成及工作原理 ,针对肢体肌肉的非线性时变性 ,建立了带反馈控制器的迭代学习控制算法 ,即复合控制器。最后利用 FNS肢体运动控制平台 ,采用复合控制算法 ,对人体曲肘和曲腕运动时的关节运动 (角位移 )轨迹进行了临床实验研究。结果表明 ,采用该算法 ,不仅改善了 FNS系统的跟踪性能 ,而且肢体运动轨迹稳定、平滑 ,受试者无任何不良生理反应 ,具有较强的自适应性。

FNS system operated by providing computer-controlled electrical stimuli via electrodes to paralyzed muscles is a medical rehabilitative engineering for people with neurological disorders.In this paper,the basic principles and the structure of FNS system are given firstly .In the light of the nonlinear phenomena of limb muscles,the iterative learning control mixed with feedback controller is proposed,which is,in fact,FNS complex controller.The general expressions associated with both feedback controller and iterative learning controller are given.Based on multi-purpose FNS limb motion control system,the clinical experiments on motion trajectory following of both elbow flexion and wrist flexion were conducted by means of the adaptive iterative learning algorithm.The results of clinical studies have demonstrated that the proposed algorithm is suitable for improving the dynamic response characteristics and stabilizing limb motion.Furthermore,the stimulated patients do not have any bad physiological reactions because the output electrical stimulation pulses vary gently.