• DocumentCode
    2535555
  • Title

    Multiple-model control of pH neutralization plant using the SOM neural networks

  • Author

    Bashivan, Pouya ; Fatehi, Alireza ; Peymani, Ehsan

  • Author_Institution
    Dept. of Control Eng., K.N. Toosi Univ. of Technol., Tehran
  • Volume
    1
  • fYear
    2008
  • fDate
    11-13 Dec. 2008
  • Firstpage
    115
  • Lastpage
    119
  • Abstract
    A multiple-model adaptive controller is developed using the self-organizing map (SOM) neural network. The considered controller which we name it as multiple controller via SOM (MCSOM) is evaluated on the pH neutralization plant. An improved switching algorithm based on excitation level of plant has also been suggested for systems with noisy environments. Identification of pH plant using SOM is discussed and performance of the multiple-model controller is compared to the self tuning regulator (STR) controller.
  • Keywords
    adaptive control; chemical industry; neurocontrollers; pH control; pole assignment; process control; self-organising feature maps; time-varying systems; SOM neural network; excitation level; improved switching algorithm; multiple-model adaptive controller; noisy environment; pH neutralization plant; pole placement; self tuning regulator controller; self-organizing map; Adaptive control; Automatic control; Clustering algorithms; Estimation error; Mathematical model; Neural networks; Performance analysis; Programmable control; State feedback; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    India Conference, 2008. INDICON 2008. Annual IEEE
  • Conference_Location
    Kanpur
  • Print_ISBN
    978-1-4244-3825-9
  • Electronic_ISBN
    978-1-4244-2747-5
  • Type

    conf

  • DOI
    10.1109/INDCON.2008.4768811
  • Filename
    4768811