• DocumentCode
    1758608
  • Title

    Neural Network Based Diagonal Decoupling Control of Powered Wheelchair Systems

  • Author

    Tuan Nghia Nguyen ; Su, Shih-Tang ; Nguyen, Hung T.

  • Author_Institution
    Fac. of Eng. & Inf. Technol., Univ. of Technol., Sydney, NSW, Australia
  • Volume
    22
  • Issue
    2
  • fYear
    2014
  • fDate
    41699
  • Firstpage
    371
  • Lastpage
    378
  • Abstract
    This paper proposes an advanced diagonal decoupling control method for powered wheelchair systems. This control method is based on a combination of the systematic diagonalization technique and the neural network control design. As such, this control method reduces coupling effects on a multivariable system, leading to independent control design procedures. Using an obtained dynamic model, the problem of the plant´s Jacobian calculation is eliminated in a neural network control design. The effectiveness of the proposed control method is verified in a real-time implementation on a powered wheelchair system. The obtained results confirm that robustness and desired performance of the overall system are guaranteed, even under parameter uncertainty effects.
  • Keywords
    biomedical equipment; handicapped aids; medical control systems; neurocontrollers; patient rehabilitation; wheelchairs; advanced diagonal decoupling control method; coupling effects; dynamic model; independent control design procedures; multivariable system; neural network based diagonal decoupling control; neural network control design; overall system performance; parameter uncertainty effects; plant´s Jacobian calculation; powered wheelchair systems; real-time implementation; systematic diagonalization technique; DC motors; Equations; Jacobian matrices; Neural networks; Vehicle dynamics; Wheelchairs; Wheels; Diagonalization technique; multivariable control system; neural network control; powered wheelchair;
  • fLanguage
    English
  • Journal_Title
    Neural Systems and Rehabilitation Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1534-4320
  • Type

    jour

  • DOI
    10.1109/TNSRE.2013.2276456
  • Filename
    6584832