基于BP网络的康复机器人的智能控制技术

Intellectual control technology of rehabilitant robot based on back propagation neural network

建立了5自由度上肢康复机器人的BP神经网络控制模型。在此模型基础上,通过对正常人肌电信号的训练学习,修正了网络权值,得到了较为理想的控制模型。最后,通过病人的肌电信号,得到了良好的输出结果。仿真实例表明,BP神经网络方法比传统方法收敛快,学习精度高,且具有较好的网络泛化能力,可以用于5自由度上肢康复机器人的智能控制。

The back propagation （BP） neural network model of 5-degree of freedom （IX）F） upper limb rehabilitant robot was built. On the basis of the model, the weight of tile network was adjusted through training and studying the electromyography （EMG） signal of normal people and the ideal control model was obtained. At last, the well output effect was gotten by the EMG signal of patients. The simulation instances show that the method of BP neural network converges faster than the conventional method and its accuracy is higher. The capacity of network generalization is better. This method can be used in the intellectual control of 5-DOF upper limb rehabilitant robot,