Design of PSO fuzzy Neural Network control for Ball and Plate system
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Dong, Xiucheng, Zhao, Yunyuan, Xu, Yunyun, Zhang, Zhang and Shi, Peng (2011) Design of PSO fuzzy Neural Network control for Ball and Plate system. International Journal of Innovative Computing, Information and Control, 7 (12). pp. 7091-7103. ISSN 1349-4198
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 optimzation (PSO) of global searching ability and the online radius basis function (RBF) algorithm ability of local searching. Then, the optomized 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.
| Item type | Article |
| URI | https://vuir.vu.edu.au/id/eprint/10312 |
| Official URL | http://www.ijicic.org/ijicic-10-11107.pdf |
| Subjects | Historical > Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM) Historical > FOR Classification > 0801 Artificial Intelligence and Image Processing Historical > SEO Classification > 970118 Expanding Knowledge in Law and Legal Studies |
| Keywords | ResPubID24543, PSO algorithm, linear quadratic state feedback regulator, tracking velocity, stabilization control |
| Citations in Scopus | 40 - View on Scopus |
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