• DocumentCode
    2196643
  • Title

    Modeling of electro-hydraulic position servo system of pump-controlled cylinder based on HHGA-RBFNN

  • Author

    Qiang, Gao ; Li-jun, Ji ; Yuan-long, Hou ; Zhong-zhi, Tong ; Yong, Jin

  • Author_Institution
    Sch. of Mech. Eng. Nanjing, Univ. of Sci. & Technol., Nanjing, China
  • fYear
    2011
  • fDate
    9-11 Sept. 2011
  • Firstpage
    335
  • Lastpage
    339
  • Abstract
    To solve the problem that it is difficult to construct an exact mathematic model for the electro-hydraulic position servo system of a pump-controlled cylinder with nonlinearity and time- varying property, HHGA-RBFNN is proposed. Each chromosome only contains three parameters including the number of hidden nodes, center and width of radial basis function; so that the complexity of proposed algorithm could be decreased with the optimal solution converged. By coding the center and width of the radial basis function respectively, the convergence rate of the algorithm could be improved; by considering both the number of hidden nodes and root-mean-square error for the selection of fitness function, the structure and parameters of network are optimized simultaneously. The simulation and experimental results show that the proposed algorithm has high modeling accuracy, excellent generalization and fast convergence rate. The simulation and experimental results show that the proposed algorithm is valid and accurate.
  • Keywords
    control engineering computing; electrohydraulic control equipment; genetic algorithms; mean square error methods; position control; pumps; radial basis function networks; servomechanisms; HHGA- RBFNN; electro-hydraulic position servo system modelling; fitness function; hybrid hierarchy genetic algorithm; nonlinearity property; pump-controlled cylinder; radial basis function center; radial basis function hidden node; radial basis function neural network; radial basis function width; root-mean-square error; time-varying property; Biological cells; Convergence; Encoding; Genetic algorithms; Servomotors; Testing; Training; HHGA (Hybrid Hierarchy Genetic Algorithm); Pump-controlled cylinder; RBFNN (Radial Basis Function Neural Network);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics, Communications and Control (ICECC), 2011 International Conference on
  • Conference_Location
    Ningbo
  • Print_ISBN
    978-1-4577-0320-1
  • Type

    conf

  • DOI
    10.1109/ICECC.2011.6067769
  • Filename
    6067769