GCHP system optimal predictive control based on RBFNN and APSO algorithm - 文章详情页

作者：

Zhang, Yating (Zhang, Yating.) | Wang, Guiyang (Wang, Guiyang.) | Han, Guang (Han, Guang.)

收录：

EI Scopus

摘要：

Aiming　at　energy　consumption　saving　problem　of　ground-coupled　heat　pump　(GCHP)　system,　a　nonlinear　optimal　control　strategy　based　on　adaptive　particle　swarm　optimization　(APSO)　algorithm　and　radial　basis　function　neural　network　(RBFNN)　predictive　control　algorithm　is　proposed　in　this　paper.　This　paper　firstly　utilizes　RBFNN　for　estimating　the　GCHP　system　model　and　forecast　the　output　values,　then　calculated　the　optimal　control　inputs　of　the　GCHP　system　via　the　rolling　optimization　of　APSO　algorithm.　Finally,　the　simulation　results　show　that　this　control　strategy　can　efficiently　reduce　the　total　energy　consumption　of　the　GCHP　system.　©　2013　TCCT,　CAA.

关键词：

Adaptive control systems Energy utilization Functions Geothermal heat pumps Optimal control systems Particle swarm optimization (PSO) Radial basis function networks

作者机构：

[ 1 ] [Zhang, Yating]College of Elctronic and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 2 ] [Wang, Guiyang]College of Elctronic and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 3 ] [Han, Guang]College of Elctronic and Control Engineering, Beijing University of Technology, Beijing 100124, China

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