基于LS-SVM-FLANN的虚拟仪器系统非线性动态补偿  

LS-SVM-FLANN-Based Nonlinear Dynamic Compensation for Virtual Instrument System

作　　者：李丽娜[1] 柳洪义[1] 罗忠[1] 王菲[1] 

机构地区：[1]东北大学机械工程与自动化学院,辽宁沈阳110004

出　　处：《东北大学学报（自然科学版）》2009年第9期1305-1309,共5页Journal of Northeastern University(Natural Science)

基　　金：国家自然科学基金资助项目(50775031)

摘　　要：针对虚拟仪器系统存在的非线性动态测量误差,提出了一种新的补偿方法.该方法依据虚拟仪器系统的静态和动态标定数据,采用最小二乘支持向量机(LS-SVM)构造的函数链接型神经网络(FLANN)辨识得到静态补偿环节及动态补偿环节模型,再将其串接到原虚拟仪器系统的后面来修正其非线性特性,改善其动态特性,从而获得系统理想的输入输出特性.实验结果表明该方法用于虚拟仪器系统动态非线性误差补偿的有效性及优越性.A new compensating method is presented to eliminate nonlinear dynamic error of virtual instrument system. In this method, according to the static and dynamic calibrated data of virtual instrument system, the parameters of static and dynamic compensation link models are identified on the basis of the functional link artificial neural networks （FLANN） that is constructed by the least square-support vector machine（LS-SVM）, then both the compensation link models are connected in series to the original virtual instrument system so as to correct its nonlinear characteristics and improve its dynamic performance, thus obtaining the desired input/ output characteristics of the system. Test results revealed that this method is effective and superior to compensating nonlinear dynamic error for virtual instrument system.

关 键 词：虚拟仪器系统 非线性静态补偿 线性动态补偿 函数链接型神经网络 最小二乘支持向量机 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]