Adaptive Tracking Control Of Stamping Robot Based on Neural Network

摘要：

A kind of recurrent fuzzy wavelet neural network (RFWNN) is constructed by using recurrent wavelet neural network (RWNN) to realize fuzzy inference. In the network, temporal relations are embedded in the network by adding feedback connections on the first layer of the network, and wavelet basis function is used as fuzzy membership function. An adaptive control scheme based on RFWNN is proposed for the stamping robot, which dynamics is characterized with highly nonlinear. Two RFWNNs are used to identify and control the robot respectively. Simulation experiments of the joints motion to follow a straight line trajectory were made by applying proposed adaptive control scheme to verify its effectiveness.

关键词： RFWNN nolinear control dynamics stamping robot simulation

作者: Tian shi-xiang

作者单位: College of Mechanical Engineering,Donghua University,Shanghai,201620,China

会议类型: 国际会议

会议名称: 2008高等智能国际会议(2008 International Conference on Advanced Intelligence)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-18（万方平台首次上网日期，不代表论文的发表时间）