Design of PSO fuzzy neural network control for ball and plate system
Date
2011
Authors
Dong, Xiucheng
Zhao, Yunyuan
Xu, Yunyun
Zhang, Zhang
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
International Journal of Innovative Computing, Information and Control, 2011; 7(12):7091-7103
Statement of Responsibility
Xiucheng Dong, Yunyuan Zhao, Yunyun Xu, Zhang Zhang and Peng Shi
Conference Name
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.
School/Discipline
School of Electrical and Electronic Engineering
Dissertation Note
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ICIC International © 2011