A new motion control method for omnidirectional intelligent wheelchair based on improved Fuzzy Support Vector Machine - 文章详情页

作者：

Guo, W. (Guo, W..) | Jia, S. (Jia, S..) | Xu, T. (Xu, T..) | Li, X. (Li, X..)

收录：

Scopus

摘要：

This　paper　proposed　the　FSVM　(Fuzzy　Support　Vector　Machine)　based　on　affinity　to　achieve　the　intelligent　wheelchair　motion　control.　The　gravity　center,　which　can　be　computed　by　calculating　the　weights　of　four　force　sensors　under　the　wheelchair　seat,　is　the　key　factor　to　determine　the　intention　of　movement　of　the　user.　The　improved　fuzzy　membership　function　of　FSVM　can　reduce　the　effect　of　clustering　gravity　center　caused　by　abnormal　clustering　gravity　center　data　generated　from　malfunction.　Comparing　with　the　traditional　SVM　(Support　Vector　Machine),　the　improved　FSVM　algorithm　has　lower　error　rate.　This　paper　further　validates　the　practical　feasibility　and　validity　of　the　proposed　control　algorithm.　The　experiment　results　show　that　the　proposed　algorithm　can　improve　the　precision　of　omnidirectional　intelligent　wheelchair　motion　control.　©　2015　IEEE.

关键词：

affinity; coordinate of gravity center; FSVM; intelligent wheelchair

作者机构：

[ 1 ] [Guo, W.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [Guo, W.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, 100124, China
[ 3 ] [Guo, W.]Engineering Research Center of Digital Community, Ministry of Education, Beijing, 100124, China
[ 4 ] [Jia, S.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 5 ] [Jia, S.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, 100124, China
[ 6 ] [Jia, S.]Engineering Research Center of Digital Community, Ministry of Education, Beijing, 100124, China
[ 7 ] [Xu, T.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 8 ] [Xu, T.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, 100124, China
[ 9 ] [Xu, T.]Engineering Research Center of Digital Community, Ministry of Education, Beijing, 100124, China
[ 10 ] [Li, X.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 11 ] [Li, X.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, 100124, China
[ 12 ] [Li, X.]Engineering Research Center of Digital Community, Ministry of Education, Beijing, 100124, China

通讯作者信息：

电子邮件地址：

查看成果更多字段

成果类型
所属机构

所有年份指定年份从至