An improved recurrent neural network and its application in nonlinear control - Details

Author：

Chen, Qili (Chen, Qili.) | Han, Honggui (Han, Honggui.) (Scholars：韩红桂) | Qiao, Lunfei (Qiao, Lunfei.)

Indexed by：

EI Scopus

Abstract：

This　paper　proposed　a　new　recurrent　neural　network　(RNN)　model.　Combining　RNN　and　state　feedback　predictive　control,　this　paper　proposed　a　predictive　control　algorithm　based　on　RNN.　The　algorithm　uses　the　output　of　RNN　as　predictive　model　to　calculate　the　predictive　value　of　state　and　output　which　were　then　calibrated　by　measurable　process　variables,　at　last,　using　the　calibrated　values　to　work　out　the　control　law　of　the　whole　system　through　optimal　control　theory.　This　algorithm　was　applied　in　wastewater　treatment　control　system　and　some　simulations　according　to　different　disturbances　and　set　values　were　presented　to　illustrate　its　utility.　©　2010　IEEE.

Keyword：

State feedback Recurrent neural networks Biomimetics Wastewater treatment Computation theory Control theory Convergence of numerical methods

Author Community：

[ 1 ] [Chen, Qili]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [Han, Honggui]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 3 ] [Qiao, Lunfei]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China