传感技术学报Issue(8)：1121-1125,5.DOI:10.3969/j.issn.1004-1699.2013.08.017
基于T-S模糊神经网络的齿槽效应补偿方法研究*
Study on Slot Effect Compensation Based on T-S Fuzzy Neural Network*
摘要
Abstract
A method is proposed to solve the slot effect problem. In this method,coils are arranged in probe of the gap sensor to detect the relative position in a tooth-groove period. A compensator based on T-S fuzzy neural network is designed to compensate the output of the gap sensor by using the relative position signal. Simulation results show that this compensator could provide correct gap data with the error less than±0. 2 mm and the output of the compensator is independent to the tooth-groove position. The precision accuracy of the sensor is increased with this method and the compensated output of the gap sensor may meet the requirement of levitation control system perfectly.关键词
间隙传感器/齿槽效应/T-S模型/模糊神经网络/高速磁浮列车Key words
gap sensor/slot effect/Takagi-Sugeno model/fuzzy function neural network(FNN)/high-speed maglev train分类
通用工业技术引用本文复制引用
靖永志,肖建..基于T-S模糊神经网络的齿槽效应补偿方法研究*[J].传感技术学报,2013,(8):1121-1125,5.基金项目
国家自然科学基金项目(51007075,51177137) （51007075,51177137）
