Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/83327
Type: | Journal article |
Title: | Design of PSO fuzzy neural network control for ball and plate system |
Author: | Dong, Xiucheng Zhao, Yunyuan Xu, Yunyun Zhang, Zhang |
Citation: | International Journal of Innovative Computing, Information and Control, 2011; 7(12):7091-7103 |
Publisher: | ICIC International |
Issue Date: | 2011 |
ISSN: | 1349-4198 |
School/Discipline: | School of Electrical and Electronic Engineering |
Statement of Responsibility: | Xiucheng Dong, Yunyuan Zhao, Yunyun Xu, Zhang Zhang and Peng Shi |
Abstract: | The 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. |
Keywords: | Ball and plate; Fuzzy neural network; PSO algorithm; PID |
Rights: | ICIC International © 2011 |
Published version: | http://www.ijicic.org/10-11107-1.pdf |
Appears in Collections: | Electrical and Electronic Engineering publications |
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