Design of PSO fuzzy neural network control for ball and plate system

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dc.contributor.authorDong, Xiuchengen
dc.contributor.authorZhao, Yunyuanen
dc.contributor.authorXu, Yunyunen
dc.contributor.authorZhang, Zhangen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.date.issued2011en
dc.description.abstractThe ball and plate system is a typical multi-variable plant, which is the extension of the traditional ball and beam problems. Particle swarm optimization algorithm fuzzy neural network control (PSO-FNNC) scheme is introduced for the ball and plate system. The fuzzy neural network (FNNC) is optimized by the offline particle swarm optimization (PSO) of global searching ability, and the online radius basis function (RBF) algorithm ability of local searching. Then, the optimized fuzzy RBF neural network (FRBF) tuned PID controller. The simulation results demonstrate the potential of the proposed technique, especially tracking speed, tracking accuracy and robustness, is improved obviously, which embodies the nice characters of the PSO-FNNC scheme.en
dc.description.statementofresponsibilityXiucheng Dong, Yunyuan Zhao, Yunyun Xu, Zhang Zhang and Peng Shien
dc.identifier.citationInternational Journal of Innovative Computing, Information and Control, 2011; 7(12):7091-7103en
dc.identifier.issn1349-4198en
dc.identifier.urihttp://hdl.handle.net/2440/83327
dc.language.isoenen
dc.publisherICIC Internationalen
dc.rightsICIC International © 2011en
dc.source.urihttp://www.ijicic.org/10-11107-1.pdfen
dc.subjectBall and plate; Fuzzy neural network; PSO algorithm; PIDen
dc.titleDesign of PSO fuzzy neural network control for ball and plate systemen
dc.typeJournal articleen

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