首页 | 本学科首页   官方微博 | 高级检索  
   检索      

弹性BP神经网络消除轮速传感器误差方法的研究
引用本文:张玘,谢秀芬,刘国福,刘波.弹性BP神经网络消除轮速传感器误差方法的研究[J].国防科技大学学报,2008,30(3):131-135.
作者姓名:张玘  谢秀芬  刘国福  刘波
作者单位:国防科技大学,机电工程与自动化学院,湖南,长沙,410073
摘    要:汽车轮速是汽车运动状态参数的主要信息源,是控制系统的核心,其精度直接影响这些系统的性能.为了提高轮速的精度,降低传感器的研制成本,提出了一种基于弹性BP神经网络的误差分析方法消除轮速传感器误差.将改进的BP神经网络--弹性BP神经网络用于误差分析,并提出误差匹配的算法.理论和仿真结果表明,该方法使绝对误差达到2×10-4>rad,能够有效地消除传感器误差,提高轮速信号的精度.

关 键 词:弹性BP神经网络  轮速传感器  误差  弹性  神经网络  轮速传感器  误差匹配  方法  研究  BP  Neural  Network  Resilient  Based  Errors  Sensor  Speed  Wheel  轮速信号  仿真结果  理论  算法  改进  误差分析  研制成本
收稿时间:2007/11/19 0:00:00

Research on Attenuating the Wheel Speed Sensor Errors Based on Resilient BP Neural Network
ZHANG Qi,XIE Xiufen,LIU Guofu and LIU Bo.Research on Attenuating the Wheel Speed Sensor Errors Based on Resilient BP Neural Network[J].Journal of National University of Defense Technology,2008,30(3):131-135.
Authors:ZHANG Qi  XIE Xiufen  LIU Guofu and LIU Bo
Institution:ZHANG Qi,XIE Xiu-fen,LIU Guo-fu,LIU Bo(College of Mechatronics Engineering , Automation,National Univ.of Defense Technology,Changsha 410073,China)
Abstract:Being the main source of vehicles' movement state parameters,wheel speed is central for control systems and its accuracy affects their performance.In order to attenuate the wheel speed sensor errors and reduce the research and manufacture cost,an error estimation method based on resilient back propagation(BP) is presented.The improved resilient BP neural network is applied to estimate the sensor errors.Matching algorithm is illustrated to realize the corresponding errors.Theoretical analysis and simulation ...
Keywords:resilient back propagation neural network  wheel speed sensor  error  
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《国防科技大学学报》浏览原始摘要信息
点击此处可从《国防科技大学学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号