Chang G C, Luh J J, Liao G D, Lai J S, Cheng C K, Kuo B L, Kuo T S
Department of Electrical Engineering, National Taiwan University, R.O.C.
IEEE Trans Rehabil Eng. 1997 Mar;5(1):2-11.
A neuro-control system was designed to control the knee joint to move in accordance with the desired trajectory of movement through stimulation of quadriceps muscle. This control system consisted of a neural controller and a fixed parameter proportional-integral-derivative (PID) feedback controller, which was designated as a neuro-PID controller. A multilayer feedforward time-delay neural network was used and trained as an inverse model of the functional electrical stimulation (FES)-induced quadriceps-lower leg system for direct feedforward control. The training signals for neural network learning were obtained from experimentation using a low-pass filtered random sequence to reveal the plant characteristics. The Nguyen-Widrow method was used to initialize the neural connection weights. The conjugate gradient descent algorithm was then used to modify these connection weights so as to minimize the errors between the desired outputs and the network outputs. The knee joint angle was controlled with only small deviations along the desired trajectory with the aid of the neural controller. In addition, the PID feedback controller was utilized to compensate for the residual tracking errors caused by disturbances and modeling errors. This control strategy was evaluated on one able-bodied and one paraplegic subject. The neuro-PID controller showed promise as a position controller of knee joint angle with quadriceps stimulation.
设计了一种神经控制系统，通过刺激股四头肌来控制膝关节按照期望的运动轨迹移动。该控制系统由一个神经控制器和一个固定参数的比例-积分-微分（PID）反馈控制器组成，被称为神经PID控制器。使用多层前馈时延神经网络并将其训练为功能性电刺激（FES）诱导的股四头肌-小腿系统的逆模型，用于直接前馈控制。神经网络学习的训练信号通过使用低通滤波随机序列的实验获得，以揭示对象特性。采用Nguyen-Widrow方法初始化神经连接权重。然后使用共轭梯度下降算法修改这些连接权重，以最小化期望输出与网络输出之间的误差。借助神经控制器，膝关节角度仅沿着期望轨迹有小的偏差。此外，利用PID反馈控制器来补偿由干扰和建模误差引起的残余跟踪误差。在一名健全人和一名截瘫患者身上评估了这种控制策略。神经PID控制器作为通过股四头肌刺激控制膝关节角度的位置控制器显示出前景。
