A model of feedback error learning based on Kalman estimator - 文章详情页

作者：

Ruan, Xiaogang (Ruan, Xiaogang.) | Liu, Liang (Liu, Liang.) | Yu, Naigong (Yu, Naigong.) (学者：于乃功) | Ding, Mingxiao (Ding, Mingxiao.)

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EI Scopus

摘要：

Based　on　the　Feedback　error　learning　(FEL)　method　and　Michael　et　al.＇s　research　work　on　dynamical　state　estimation,　a　new　model　of　motor　control　system　is　proposed　to　overcome　the　drawback　deriving　from　time　delay.　In　the　new　model,　the　supervised　signal　derives　from　both　the　output　of　the　Kalman　estimator　and　the　feedback　motor　command,　and　this　comprehensive　signal　provides　the　instructive　information　to　train　the　forward　neural　network　in　the　cerebellar　cortex.　The　effectiveness　of　the　proposed　new　model　is　demonstrated　by　simulation　experiments　on　inverted　pendulum.　©2006　IEEE.

关键词：

Computer simulation Error analysis Feedback Information retrieval Kalman filters Learning systems Mathematical models

作者机构：

[ 1 ] [Ruan, Xiaogang]Department of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022, China
[ 2 ] [Liu, Liang]Department of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022, China
[ 3 ] [Yu, Naigong]Department of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022, China
[ 4 ] [Ding, Mingxiao]Department of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022, China

通讯作者信息：

电子邮件地址：

liuliang@emails.bjut.edu.cn

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