Neural Network Based Asynchronous Learning Control Systems
神经网络异步自学习控制系统

In this paper the neural network based asynchronous learning control system,on the basis of the asynchronous learning control method given by ref. 1], is proposed. The gradient-type learning control algorithm is derived, the strict proof on stability convergency is provided by Lyapunov stability theory, and the simulation study of two links of PUMA 560 robot systems is given. The results show that the RMS track accuracy of this proposed method is improved greatly compared to classical PID control.