• 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