• DocumentCode
    2737357
  • Title

    Adaptive type-2 fuzzy control of non-linear systems

  • Author

    Mosè, Galluzzo ; Bartolomeo, Cosenza

  • Author_Institution
    Dipt. di Ing. Chimica dei Processi e dei Mater., Univ. degli Studi di Palermo, Palermo, Italy
  • Volume
    2
  • fYear
    2009
  • fDate
    20-22 Nov. 2009
  • Firstpage
    705
  • Lastpage
    709
  • Abstract
    The paper describes the development of two different type-2 adaptive fuzzy logic controllers and their use for the control of a non linear system that is characterized by the presence of bifurcations and parameter uncertainty. Although a type-2 fuzzy logic controller is able to handle the non linearities and the uncertainties present in a system, its robustness and effectiveness can be increased by the use of an opportune adaptive algorithm. A simulation study was conducted to compare the behavior of adaptive controllers with that of simple type-1 and type-2 fuzzy logic controllers. The system to be controlled, used for the simulation, is a continuous bioreactor for the treatment of mixed wastes in which a culture of Pseudomonas Putida is carried out while phenol and glucose are carbon and energy sources. From simulations results it can be seen that both adaptive controllers, but in particular the self tuning controller, have a better performance being able to eliminate oscillations that are present with basic fuzzy controllers.
  • Keywords
    adaptive control; control nonlinearities; fuzzy control; robust control; self-adjusting systems; uncertain systems; Pseudomonas Putida; bifurcations; carbon sources; energy sources; nonlinear systems; parameter uncertainty; system robustness; type-2 adaptive fuzzy logic controllers; Adaptive control; Bifurcation; Control systems; Fuzzy control; Fuzzy logic; Linear systems; Linearity; Programmable control; Uncertain systems; Uncertainty; adaptive control; non linear systems; type-2 fuzzy logic control; uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-4754-1
  • Electronic_ISBN
    978-1-4244-4738-1
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2009.5358311
  • Filename
    5358311