基于径向基函数网络的光电编码器误差补偿法  

Error compensation of optical encoder based on RBF network

作　　者：洪喜[1] 续志军[1] 杨宁[1] 

机构地区：[1]中国科学院长春光学精密机械与物理研究所

出　　处：《光学精密工程》2008年第4期598-604,共7页Optics and Precision Engineering

基　　金：国家自然科学基金资助项目(No.60574089)

摘　　要：提出了一种新的编码器误差修正技术。建立了径向基函数网络模型，以高精度检测仪器的检测值为学习目标，以生成最小映射误差为原则调节网络权因子、径向基函数中心和宽度，使建立的网络具有良好的学习能力和泛化能力。利用DSP的在线烧写技术保存网络建模参数，从而无需拆改编码器系统即可实现误差的补偿与修正，并且可根据使用需要进行程序更新。仿真和实验表明，采用此种方法可将编码器的精度提高至原来的1～3倍，有效地改善了编码器的系统精度，并且很好地解决了非线性误差对系统的影响。A new method to correct and compensate the dynamic error of a optical encoder was presented by using the neural network and the digital signal process technology. A modeling method based on the Radial Basis Function（RBF） was set up, in which the output was the test value of high precision instrument and the input was the angle values of sample points. According to the inhibiting condition between the test value and the output of network, the power factor formula, the center and width of the RBF were adjusted to make the model have a good learning ability and a generalization ability. The relationship between sampled angles and errors was determined by training the neural network. After the sampled angles were measured, the unknown error of the encoder could be calculated via a trained neural network even if the error was nonlinear. The tested results show that the precision of system error by this method is 1-3 times that by tradiotional method. And not only the error of each network point but also the interpolated network point can be corrected automatically, The practical application proves that the precision of measuring system is improved greatly by using the RBF model as error compensation, and the effect of nonlinear errors on the system is reduced also.

关 键 词：光电编码器 神经网络 径向基函数 误差补偿 数字信号处理器 

分 类 号：TN762[电子电信—电路与系统] TP183[自动化与计算机技术—控制理论与控制工程]