Motorized and Functional Electrical Stimulation Induced Cycling via Switched Repetitive Learning Control

Motorized and Functional Electrical Stimulation Induced Cycling via Switched Repetitive Learning Control
复制标题

DOI:
10.1109/tcst.2018.2827334
复制
发表时间:
2019-07-01
影响因子:
4.8
通讯作者:
Dixon, Warren E.
Dixon, Warren E.
中科院分区:
计算机科学2区
文献类型:
--
作者:
Duenas, Victor H.;Cousin, Christian A.;Dixon, Warren E.

文献摘要

被引文献

相似文献

通过功能性电刺激(FES)结合机动辅助诱导的骑自行车是一种很有前途的康复策略。开发了一种开关控制器,该控制器基于曲柄角度激活电动机旁边的下肢肌肉,以促进骑自行车。针对自行车运动中踏频跟踪的周期性特点,设计了一种重复学习控制器(RLC),用于在已知周期内跟踪期望的踏频轨迹。RLC开发的不确定性,非线性骑自行车系统的自主状态相关切换。电刺激基于整个曲柄循环的扭矩有效性在多个下肢肌肉群之间切换。当肌肉群产生低扭矩时,电动马达提供帮助。一个基于李雅普诺夫的稳定性分析,调用最近开发的拉萨尔-吉泽推论的非光滑系统是用来保证渐近跟踪。开发的控制器进行了测试,在五个健全的个人和三个参与者的神经系统疾病的FES循环实验。RLC在节奏跟踪中的附加值通过比较有和没有学习前馈项的两次试验的结果来说明。结果表明,RLC产生较低的平均均方根的节奏跟踪误差。
Cycling induced by functional electrical stimulation (FES) coupled with motorized assistance is a promising rehabilitative strategy. A switching controller that activates lower limb muscles alongside an electric motor based on the crank angle is developed to facilitate cycling. Due to the periodic nature of cadence tracking in cycling, a repetitive learning controller (RLC) is developed to track a desired cadence trajectory with a known period. The RLC is developed for an uncertain, nonlinear cycle-rider system with autonomous state-dependent switching. Electrical stimulation switches across multiple lower limb muscle groups based on the torque effectiveness throughout the crank cycle. The electric motor provides assistance when the muscle groups yield low torque production. A Lyapunov-based stability analysis that invokes a recently developed LaSalle-Yoshizawa corollary for nonsmooth systems is used to guarantee asymptotic tracking. The developed controller was tested during FES-cycling experiments in five able-bodied individuals and three participants with neurological conditions. The added value of the RLC in cadence tracking is illustrated by comparing the results of two trials with and without the learning feedforward term. The results indicate that the RLC yields a lower mean root-mean-squared cadence tracking error.