Error Compensation of Photoelectric Encoder Based on Improved BP Neural Network

摘要：

A new method to correct and compensate the error of a photoelectric encoder was presented by using the neural network. A modeling method based on the Back Propagation (BP) was set up, in which the output follows the test value of high precision instrument and the input was the angle of sample points. The connecting weights of hidden layer and output layer were modified according to the steepest descent method. Momentum term was introduced to neural network to avoid oscillation, variable step length was suggested to accelerate study speed and avoid local optimum. Experiments showed that the precision of measuring system was improved greatly by using the BP model as error compensation, and the effect of nonlinear errors on the system was also reduced.

关键词： photoelectric encoder BP neural network error compensation

作者: WANG Xiao-gang CAI Tao DENG Fang XU Li-shuang

作者单位: School of Automation, Beijing Institute of Technology, Beijing, 100081 Key Laboratory of Complex Sys School of Automation, Beijing Institute of Technology, Beijing, 100081 Key Laboratory of Complex Sys

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 3958-3963

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）