NEURAL-NETWORK CONTROL OF FUNCTIONAL NEUROMUSCULAR STIMULATION SYSTEMS - COMPUTER-SIMULATION STUDIES
NEURAL-NETWORK CONTROL OF FUNCTIONAL NEUROMUSCULAR STIMULATION SYSTEMS - COMPUTER-SIMULATION STUDIES
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DOI：
10.1109/10.469379
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发表时间：
1995-11-01
影响因子：
4.6
通讯作者：
CHIZECK, HJ
中科院分区：
文献类型：
--
作者：
ABBAS, JJ;CHIZECK, HJ
为控制功能性神经肌肉刺激（FNS）系统中的循环运动，设计了一种神经网络控制系统。该设计直接解决了FNS控制系统中的三个主要问题：为特定个体定制控制系统参数，在操作过程中适应肌肉骨骼系统的变化，以及获得对机械干扰的抵抗力。控制系统采用自适应前馈和反馈控制技术相结合的两阶段神经网络实现。开发了一种新的学习算法，以提供快速定制和自适应。在计算机模拟肌肉骨骼模型的一系列研究中对控制系统进行了评估。研究中使用的电刺激肌肉模型包括非线性招募，线性动力学，乘法非线性扭矩-角度和扭矩-速度比例因子。该模型由关节运动被动约束的单段平面系统构成。评估结果表明，该控制系统能够为给定的肌肉骨骼系统提供自动定制的前馈控制器参数，能够通过在线调整前馈控制器参数来解释肌肉骨骼系统的变化，并且能够抵抗机械干扰的影响。这些结果表明，这种设计可能适用于FNS系统和其他动态系统的控制。
A neural network control system has been designed for the control of cyclic movements in Functional Neuromuscular Stimulation (FNS) systems. The design directly addresses three major problems in FNS control systems: customization of control system parameters for a particular individual, adaptation during operation to account for changes in the musculoskeletal system, and attaining resistance to mechanical disturbances. The control system was implemented by a two-stage neural network that utilizes a combination of adaptive feedforward and feedback control techniques. A new learning algorithm was developed to provide rapid customization and adaptation. The control system was evaluated in a series of studies on a computer simulated musculoskeletal model. The model of electrically stimulated muscle used in the study included nonlinear recruitment, linear dynamics, and multiplicative nonlinear torque-angle and torque-velocity scaling factors. The skeletal model consisted of a one-segment planar system with passive constraints on joint movement. Results of the evaluation have demonstrated that the control system can provide automated customization of the feedforward controller parameters for a given musculoskeletal system, It can account for changes in the musculoskeletal system by adapting the feedforward controller parameters on-line and it can resist the effects of mechanical disturbances. These results suggest that this design may be suitable for the control of FNS systems and other dynamic systems.