Nonlinear internal model control with inverse model based on extreme learning machine - Details

author：

Huang, Yanwei (Huang, Yanwei.) ^[1] (Scholars：黄宴委) | Wu, Dengguo (Wu, Dengguo.) ^[2]

Indexed by：

EI Scopus

Abstract：

Extreme　learning　machine　is　a　novel　single　hidden　layer　feedforward　neural　networks　with　a　strong　abilities,　for　example　simple　net　structure,　fast　learning　speed,　good　generalization　and　so　on.　Aimed　at　the　system　with　a　delay　unit,　A　new　control　strategy　for　internal　model　control　is　proposed　to　set　up　an　inverse　model　of　the　minimal　phase　subsystem　by　using　extreme　learning　machine　with　in-out　system　datum.　Moreover,　the　relative　stable　error　for　internal　model　control　system　with　a　delay　unit　is　presented　to　evaluate　the　system　performance.　The　features　for　the　internal　model　control　system　based　on　extreme　learning　machine　are　compared　with　that　based　on　neural　network.　The　experimental　results　indicate　that　the　internal　model　control　system　based　on　extreme　learning　machine　has　small　stable　error　and　strong　robustness.　©　2011　IEEE.

Keyword：

Control systems Errors Feedforward neural networks Knowledge acquisition Machine learning Model predictive control Multilayer neural networks Network layers

Community：

[ 1 ] [Huang, Yanwei]School of Electric Engineering and Automation, Fuzhou University, Fuzhou, China
[ 2 ] [Wu, Dengguo]School of Electric Engineering and Automation, Fuzhou University, Fuzhou, China

Reprint 's Address：

Email：

sjtu_huanghao@fzu.edu.cn

Show more details

Version：