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
Link To Document :
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