DocumentCode
3458986
Title
Applying Genetic Algorithm to On-Line Updated PID Neural Network Controllers for Ball and Plate System
Author
Dong, Xiucheng ; Zhang, Zhang ; Chen, Chao
Author_Institution
Provincial Key Lab. on Signal & Inf. Process., Xihua Univ., Xihua, China
fYear
2009
fDate
7-9 Dec. 2009
Firstpage
751
Lastpage
755
Abstract
The PID (proportional-integral-derivative) neural network (PIDNN) controller based on genetic algorithm (GA) for ball and plate system is proposed in this paper. Genetic algorithm is applied in training weighting factor of multilayered forward neural network, thus the disadvantage of BP algorithm that easily fall into partial extreme value can be overcome and at the same time, the advantage of PID neural network controller that has simple structure and good dynamic and static performance is provided with. The simulation results show that the proposed controller has the adaptability, strong robustness and satisfactory control performance in the ball and plate system.
Keywords
backpropagation; genetic algorithms; multivariable control systems; neurocontrollers; robust control; three-term control; BP algorithm; ball-plate system; genetic algorithm; multilayered forward neural network; online updated PID neural network controllers; proportional-integral-derivative neural network; training weighting factor; Control systems; Fuzzy control; Genetic algorithms; Multi-layer neural network; Neural networks; Neurons; Pi control; Proportional control; Sliding mode control; Three-term control;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on
Conference_Location
Kaohsiung
Print_ISBN
978-1-4244-5543-0
Type
conf
DOI
10.1109/ICICIC.2009.113
Filename
5412475
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