Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/75803
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dc.contributor.authorLiu, D.-
dc.contributor.authorDong, X.-
dc.contributor.authorShi, P.-
dc.date.issued2012-
dc.identifier.citationICIC Express Letters, Part B: Applications, 2012; 3(5):1259-1267-
dc.identifier.issn2185-2766-
dc.identifier.urihttp://hdl.handle.net/2440/75803-
dc.description.abstractThe fuzzy RBF neural network control scheme based on a tree structure membrane optimization algorithm (TMO-FRBF) is introduced in this paper. The improved optimization algorithm is combined with the tree structure and membrane computing. The fuzzy RBF neural network (FRBF) is optimized by the improved membrane optimization algorithm, then the optimized FRBF tuned proportional-integral-derivative (PID) controller for ball-plate system which is a typical multi-variable plant. The simulation results demonstrate the potential of the improved algorithm, compared with the FRBF optimized by the standard particle swarm optimization algorithm, we can see the tracking speed, robustness and control efficiency are improved, which embody the nice characters of the TMO-FRBF control scheme. © 2012 ICIC International.-
dc.description.urihttp://www.ijicic.org/elb-3%285%29.htm-
dc.language.isoen-
dc.publisherICIC International-
dc.rightsCopyright status unknown-
dc.titleThe optimization based on improved membrane algorithm for fuzzy RBF neural network control of ball-plate system-
dc.typeJournal article-
pubs.publication-statusPublished-
dc.identifier.orcidShi, P. [0000-0001-8218-586X]-
Appears in Collections:Aurora harvest
Electrical and Electronic Engineering publications

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