Abbas J J, Chizeck H J
Biomedical Engineering Program, Catholic University of America, Washington, D.C. 20064, USA.
IEEE Trans Biomed Eng. 1995 Nov;42(11):1117-27. doi: 10.1109/10.469379.
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.
已设计出一种神经网络控制系统，用于控制功能性神经肌肉刺激（FNS）系统中的周期性运动。该设计直接解决了FNS控制系统中的三个主要问题：针对特定个体定制控制系统参数、在运行过程中进行调整以适应肌肉骨骼系统的变化以及实现对机械干扰的抗性。该控制系统由一个两级神经网络实现，该网络采用了自适应前馈和反馈控制技术的组合。开发了一种新的学习算法，以实现快速定制和调整。在一系列针对计算机模拟肌肉骨骼模型的研究中对该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募集、线性动力学以及乘法非线性扭矩 - 角度和扭矩 - 速度缩放因子。骨骼模型由一个单节段平面系统组成，对关节运动有被动约束。评估结果表明，该控制系统可以为给定的肌肉骨骼系统自动定制前馈控制器参数。它可以通过在线调整前馈控制器参数来适应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。
