%0 Journal Article
%T Neural Network Based Asynchronous Learning Control Systems<br>神经网络异步自学习控制系统
%A Deng Zhidong
%A Sun Zhenqi
%A Liu Jianwei
%A <br>邓志东
%A 孙增圻
%A 刘建伟
%J 自动化学报
%D 1995
%I 
%X 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.
%K Neural network and intelligent control
%K asynchronous learning control
%K Lyapunov stability theory
%K learning algorithm
%K robot control<br>神经网络
%K 异步自学习控制
%K 学习控制系统
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=9DC71E9B3D9B259DF0E5B48331EC20AA&yid=BBCD5003575B2B5F&vid=659D3B06EBF534A7&iid=94C357A881DFC066&sid=E4EC39E73004B593&eid=06F643376BC2509E&journal_id=0254-4156&journal_name=自动化学报&referenced_num=3&reference_num=5